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School's Over: Learning Spaces in Europe in 2020:
An Imagining Exercise on the Future of Learning
Authors: Riel Miller, Hanne Shapiro and Knud Erik Hilding-Hamann
Editors: Yves Punie, Kirsti Ala-Mutka and Christine Redecke
r
EUR 23532 EN - 2008
The mission of the IPTS is to provide customer-driven support to the EU policy-making
process by researching science-based responses to policy challenges that have both a socio-
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Institute for Prospective Technological Studies
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JRC4 7412
EUR 23532 EN
ISBN 978-92-79-10053-6
ISSN: 1018-5593
DOI 10.2791/54506
Luxembourg: Office for Official Publications of the European Communities
© European Communities, 2008
Reproduction is authorised provided the source is acknowledged
Printed in Spain
Acknowledgments
This report, written by Riel Miller (www.rielmiller.com), Hanne Shapiro and Knud Erik Hilding-
Hamann (www.danishtechnology.dk ), is based on the fourth and final deliverable in the contract
‘Learning spaces in 2020: Future learning in the Knowledge Based Society in Europe Enabled by
Information and Communication Technology (ICT)’, Contract No. 150542-2006 F1SC DK, IPTS,
European Commission.
The authors of the report wish to thank particularly Yves Punie as well as Marcelino Cabrera, Clara
Centeno, and Kirsti Ala-Mutka – all at IPTS in Seville, the participants at the Hybrid Strategic
Scenario Workshop held in Paris, February 12 and 13, 2007 (see Annex 2 for a full list), outside
reviewers Charles Pascal, Philip van Notten and others listed in Annex 3, and Saul Shapiro for
editing the final report. Special thanks are also due to Jean Wemaere, President, Demos France and
Jean Claude Ruano-Borbalan, former Director of Demos Institut, France for hosting the two day
Hybrid Strategic Scenario workshop in Paris. Lastly we would like to express deep appreciation to
Hanne Shapiro whose dedication and support made this report possible.
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Preface
This report provides a visionary scenario of a 21st Century Learning-intensive Society where
Learning Spaces are the next school. It is an imaginary snapshot of learning in Europe in 2020 which
has been developed on the basis of a rigorous foresight approach. It presents a discontinuous model
of how people learn and how what they learn is used in everyday life. The vision provokes and
challenges the assumptions that currently dominate, often implicitly, the choices being made today. It
includes hypothetical policy options for the imagined Learning-intensive Society Learning Spaces.
The visionary scenario and the policy options that are part of it are intended to provide food for
thought on the possible future of learning in Europe in 2020.
“Learning Spaces” (LS) is the term used in a report published in 2006 by the European Commission's
Institute for Prospective Technological Studies, “as a way to embrace a different view of future
learning”.1 The current report moves the discussion of Learning Spaces forward. It is written by Riel
Miller (www.rielmiller.com), Hanne Shapiro and Knud Erik Hilding-Hamann
(www.danishtechnology.dk ) and is the result of a study commissioned by IPTS.
1 Punie, Y. & Cabrero, M., 2006. The Future of ICT and Learning in the Knowledge Society. Report on a Joint DG JRC/IPTS-DG
EAC Workshop held in Seville 20-21 October 2005, DG JRC-IPTS, European Communities, March 2006, EUR 22218 EN.
ii
Photo credit: Mark Schacter – www.luxetveritas.ca
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“The conception of education as a social process and function has no definite meaning until we
define the kind of society we have in mind.”
John Dewey, Democracy and Education, 1915
Miss Viola: “Good morning class!”
Class: “Good morning Miss Viola!”
Miss Viola: “Today we begin with the most important lesson you will ever learn at Penguin
Elementary. Does anyone know what that is?”
Hugh: “We have to find our Heart Song all by ourselves.”
Miss Viola: “Well done Hugh.”
Hugh: “It is the voice you hear inside.”
Miss Viola: “Yes!”
Hugh: “Who you truly are!”
Miss Viola: “Yes! So, take a moment and let it come to you.”
There is a pause, then a clamour.
Class: “I got one!”, “I got one!”, “I got one!”, “Pick me”, “Pick me”, “Me”
Miss Viola: “Okay, Seymour”
Singing starts: “Don’t push me ‘cause I’m close to the edge, I’m trying not to lose my head…”
The scene from the film Happy Feet when the young penguins start the lifelong development of their
Heart Song, Warner Brothers, 2007
“Articulate human groups share a natural human inclination to attach universal significance to their
own experiences. The pattern is not inherent in the events themselves; it is imposed upon them out of
the consciousness and experience of the historian. The pattern is, however, determined not so much
by the historian’s view of the present as by his view of the future. Past and future are the two
essential time dimensions; the present is an infinitesimally small moving point on a continuous line
consisting of past and future. It is thus the future prospect even more than the present reality which
shapes the historian’s view of the past.”
E.H. Carr, “The New Society”, Macmillan, 1951, Pp. 12.
Table of Contents
EXECUTIVE SUMMARY ............................................................................................................................................VII
1 WHY THINK ABOUT THE FUTURE OF LEARNING SPACES NOW?......................................................... 1
2 SIGNS OF A CHANGING CONTEXT FOR LEARNING................................................................................... 1
2.1 MACRO-LEVEL TRENDS AND DRIVERS ................................................................................................................ 2
2.1.1 New skills and competences.......................................................................................................................... 2
2.1.2 Demographic changes................................................................................................................................... 4
2.1.3 Globalization ................................................................................................................................................ 5
2.1.4 Macro-level observations.............................................................................................................................. 6
2.2 MESO-LEVEL TRENDS AND DRIVERS ................................................................................................................... 7
2.2.1 Formal versus informal learning .................................................................................................................. 7
2.2.2 Educational reform – how far can it go?.................................................................................................... 10
2.2.3 Workplace learning – formalizing informality?.......................................................................................... 11
2.2.4 Meso-level observations.............................................................................................................................. 12
2.3 MICRO-LEVEL TRENDS AND DRIVERS ............................................................................................................... 12
2.3.1 Diversification of life: are learning cultures changing?............................................................................. 13
2.3.2 Micro-level observations............................................................................................................................. 16
2.4 TECHNOLOGICAL TRENDS AND DRIVERS........................................................................................................... 16
2.4.1 Faster, cheaper – better?............................................................................................................................ 17
2.4.2 Technology observations............................................................................................................................. 18
2.5 SUMMARY OF TRENDS AND DRIVERS ................................................................................................................ 19
2.5.1 Impact of macro trends and drivers on learning.........................................................................................19
2.5.2 Impact of meso trends and drivers on learning........................................................................................... 20
2.5.3 Impact of micro trends and drivers on learning ......................................................................................... 20
3 USING A HYBRID STRATEGIC SCENARIO TO IMAGINE THE FUTURE OF LEARNING ................. 21
3.1 FORESIGHT METHODOLOGY – RETHINKING THE PRESENT ................................................................................. 22
3.2 BACKCASTING .................................................................................................................................................. 23
3.3 APPLYING THE HYBRID STRATEGIC SCENARIO PROCESS TO EUROPEAN LEARNING SPACES IN 2020.................. 24
3.3.1 Two frames, a canvas, and a colour palette................................................................................................ 24
3.3.2 The narrative frame .................................................................................................................................... 26
3.3.3 The “learning-intensive society” frame...................................................................................................... 27
3.3.4 A model of learning..................................................................................................................................... 28
3.3.5 Combining the learning model with the learning-intensive society model ................................................. 30
3.3.6 A generic palette of colours for describing learning spaces....................................................................... 31
4 IMAGINING THE FUTURE OF LEARNING.................................................................................................... 33
4.1 THE LEARNING-INTENSIVE SOCIETY (LIS) SCENARIO ....................................................................................... 34
4.2 LEARNING SPACES IN THE LEARNING-INTENSIVE SOCIETY ................................................................................ 37
5 FUNDAMENTAL FEATURES OF LEARNING SPACES IN THE LIS.......................................................... 39
5.1 PERSONAL DIGITAL SPACES .............................................................................................................................. 39
5.2 CONNECTING AND SOCIAL SPACES.................................................................................................................... 40
5.3 TRUSTED SPACES .............................................................................................................................................. 40
5.4 MOTIVATING AND EMOTIONAL SPACES ............................................................................................................ 41
5.5 CONTROLLABLE, CREATIVE/EXPERIMENTAL, OPEN/REFLEXIVE SPACES............................................................ 42
5.6 EVALUATED AND CERTIFIED SPACES ................................................................................................................ 43
5.7 KNOWLEDGE MANAGEMENT............................................................................................................................. 43
5.8 INCLUSIVE SPACES............................................................................................................................................ 44
5.9 THE COST OF LEARNING SPACES ....................................................................................................................... 44
6 BACKCASTING THE LIS-LS SCENARIO ........................................................................................................ 47
6.1 THE “HOW TO” SCENARIOS ............................................................................................................................... 47
6.1.1 LS specific scenarios set: socio-economic mix and referential principles.................................................. 48
6.1.2 MIT open courseware – external official certification................................................................................ 49
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6.1.3 Zagat reputational worth – scale-based meaning, data mining.................................................................. 50
6.1.4 Tribal federalism – dynamically gated communities .................................................................................. 50
6.1.5 Cosmic soup – Wikification of identity........................................................................................................ 51
6.2 COMPARING THE FUTURE OF LEARNING WITH THE PRESENT ............................................................................. 51
6.2.1 Taking care of the functions of the industrial era education system........................................................... 52
6.3 GENERAL PERFORMANCE CRITERIA FOR THE FUNCTIONING OF LS IN THE LIS ................................................. 56
6.3.1 Network fluidity and density ....................................................................................................................... 56
6.3.2 Complexity .................................................................................................................................................. 56
6.3.3 Spontaneity.................................................................................................................................................. 57
6.3.4 Creativity .................................................................................................................................................... 57
6.3.5 Wisdom........................................................................................................................................................ 58
6.3.6 LIS interdependency – the synergy conditions............................................................................................ 58
7 HYPOTHETICAL POLICY OPTIONS............................................................................................................... 61
ANNEX 1 - WORKSHOP AGENDA..............................................................................................................................65
ANNEX 2 – WORKSHOP PARTICIPANTS.................................................................................................................68
ANNEX 3 - INTERVIEWEES, COMMENTATORS AND REVIEWERS................................................................. 69
REFERENCES ................................................................................................................................................................. 71
Executive Summary
“Learning Spaces” (LS) is the term used in a report published in 2006 by the Institute for Prospective
Technological Studies, “as a way to embrace a different view of future learning”. This report moves
the discussion of Learning Spaces forward by refining the concept and linking it to possible policy
initiatives. The report builds on the premise that the context for learning is already changing, and
thus the characteristics and enabling infrastructure for learning spaces may also be changing. To
clarify the nature of these changes an advanced scenario methodology is used.
The report builds a scenario of a 21st Century Learning-intensive Society (LIS), which could emerge
from the potential of the present. The scenario is an imaginary snapshot of how society might
function with open learning at the core of what everyone does all the time, everywhere. In the LIS
scenario, Learning Spaces (LS) are the next school. It is a vision of learning that differs radically
from the conventional classroom model where blackboard knowledge and the imposing teacher
represent the quintessential learning space of the industrial era.
In the imaginary snapshot of Europe in 2020 it is assumed that society is no longer dominated by the
industrial-era logics of mass-production and mass-consumption. Scale is no longer the guiding
principle. Instead, the pivotal act, the creation of added value, has changed locations. In the
Learning-intensive Society of 2020, the daily (re)creation of the world around us through spoken or
written words, pictures and movies, will generate the largest share of added value. Weak signals of
this change are already detectable now in 2008 - there are hints of the potential of the present to
create a society where the division between the supply side and demand side is marginal. These
include tendencies towards self-generated personalization, the “unique creation” expressed in a
widespread do-it-yourself attitude, the breakdown of the professional/amateur distinction, and the
emergence of Web 2.0 technologies that give rise to social networking, collaborative content creation
and democratized innovation.
This means that the crucial moment in industrial society when the entrepreneur or engineer or
designer comes up with an idea that can then be implemented by taking advantage of economies of
scale is no longer central. The aims and organization of wealth creation no longer take on the form of
a pyramid or hierarchy, with the genius who generates new ideas and the technocrat manager who
implements them occupying the top floor, while down below at end of the chain of command is the
“front-line” worker. The Learning-intensive Society is heterarchical (antonym of hierarchical).
Everyone is the inventor and implementer of his or her own designs, the unique, personalized set of
artefacts, services, and experiences. As a result, in the Learning-intensive Society there is a profound
difference when compared to industrial society in the relationship of knowledge to production or, in
more general terms, the activities that (re)create daily life.
In 2020, Learning Spaces will enable people to construct their identities as inter-dependent and inter-
connected social beings and on this basis to produce the wealth and community that sustain their
well-being. In general terms, this functional role or purpose of learning infrastructure in 2020 is not
much different from before. It continues to serve the main economic and social requirements of
society. However, by 2020 the leading economic and social requirements have changed.
From the perspective of learning the two most marked contrasts between the vision of Learning
Spaces in a Learning-intensive Society and the current framework for learning, are (a) the
abandonment of the technocratic, hierarchical and exclusive approach to education and skill
achievement, and (b) the marginalization of institutionalized learning.
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This report describes in some detail eight attributes of Learning Spaces in a Learning-intensive
Society (LIS-LS):
Personal digital spaces
Learning-intensive Society Learning Spaces are where each and every learner can access a holistic
and life long track record of his/her learning achievements and articulate their learning ambitions
independent of time, location and access device. This is the core of LS in 2020, the anchor of a
knowledge system that records and signals what people know, what they have learned and what they
aspire to learn, at particular times and in particular places.
Connecting and social spaces
Learning-intensive Society Learning Spaces are where all learners meet physically and virtually to
share experiences and engage with other communities and social networks. Such LS are inherently
“inclusive” since everyone has access to an individual learning account and to the network linking
him/her with other learners. LS are active spaces, the place where projects unfold and experiments
take place. The range of activities is as vast as people’s motivations and imaginations – from the
banal to the sublime, the common to the exceptional. All learning counts.
Trusted spaces
Learning-intensive Society Learning Spaces are where people can easily and verifiably assess both
what other people know and what they are learning. Clarity with respect to the degree of
transparency and verifiability associated with what people know and how they learn plays a critical
role in ensuring that LS in the LIS can span a variety of different degrees of trustworthiness.
Motivating and emotional spaces
Learning-intensive Society Learning Spaces are where people access the action content of learning
across the full range of motivations and emotions that constitute learning. Both learning and
“intelligence” are multi-dimensional, encompassing a rich variety of motives and emotional states.
Learning-intensive Society Learning Spaces are complex crossroads where learners engage their
motives and emotions through the act of learning.
Controllable, creative/experimental, open/reflexive spaces
Control. Learning-intensive Society Learning Spaces are where the needs of learning and the
learner can take precedence when necessary or wanted. Everyone learns differently and in
different ways at different times about different things. LS need to be able to nurture this
diversity and make it easy for learners to discover the best way for them to learn in any
circumstance.
Creative/flexible. Learning-intensive Society Learning Spaces are characterized by a high
level of creativity and experimentation, in part, because the dualism between life and learning
diminishes when the pursuit of knowledge through experience makes the use of LS an
everyday practice. The creativity and flexibility of LS in a LIS entail experimentation and
risk taking.
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Open/reflexive. Learning-intensive Society Learning Spaces are permeable, connected, and
modular spaces that enable a wide range of learning, including synchronous and
asynchronous, face-to-face and virtual, subjective and inter-subjective. Learning-intensive
Society Learning Spaces are reflexive because in their LS a person is able to get and give
continuous, real-time meaning to the “what” and “how” of learning as it occurs, tagged with
multiple references.
Evaluated and certified spaces
Learning-intensive Society Learning Spaces are where acquired skills and competences are
demonstrated, evaluated and certified. The institutions and practices – rules, customs, habits – of
LIS-LS offer “certification” based on both hierarchical, application-based verification as well as
heterarchical, self-referential expressions of what a person knows.
LIS-LS unfold along five further dimensions which are enabling factors for their functioning:
network fluidity and density, complexity, spontaneity, creativity, and wisdom.
Hypothetical policy options for the imagined Learning-intensive Society Learning Spaces
On the basis of these observations the report offers a number of tentative and hypothetical policy
options to begin a discussion of policies that would be more consistent with the assumptions of the
Learning-intensive Society Learning Spaces, and thereby try to leverage the potential of the present
to promote future Learning Spaces. These are:
Personalized Learning Spaces and cybercitizenship. Digital learning accounts will need to be
established, with a verifiable identity that is controlled by the individual, supported by a means of
establishing identity effectively. Major milestone: a European agreement on universal access to
cybercitizenship for all citizens of the EU by 2010.
Reputation systems. Legal measures are needed to support the accumulation of trustworthy
reputations. Considerable research needs to be invested to understand the emergent reputation
systems and to find ways of integrating evaluation and feedback into the routine functioning of
people’s everyday activities. The central policy issue to be addressed concerns setting up the rules
and institutions that allow for the practical exercise of ownership over a personal record of
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competence or accumulated knowledge. This is important since it can significantly alter motivations
and incentives, which in turn facilitates the control and responsibility that makes Learning Spaces
operational. Major milestone: The first KnowBank, an institution that facilitates the evaluation and
accessibility of personal knowledge assets accumulated over a lifetime and vested in a validated and
valorised personal knowledge account, is established in Europe in 2010.
Intellectual property and transactions. Open source is fundamental to Learning-intensive Society
Learning Spaces. Current intellectual property rights (IPR) systems, transaction and payment
systems, and peer-to-peer contractual platforms all fail to address the needs of LIS-LS for sharing
and accessing knowledge. A copyleft or Creative Commons regimes, complemented by an
international standard on traceability and a public service for drawing up unique, single transaction
contracts, might be able to resolve these problems. Underlying all of these learning based transaction
relationships are payment and accounting mechanisms that are conducive to new business models
and the creation of new markets that are no longer organized on the basis of the separation of supply-
demand. Major milestone: By 2010 the European Central Bank introduces the “neuro” (net euro), a
monetary instrument, one way to facilitate internet based peer-to-peer transactions running on a new
universal system for both monetary and non-monetary net based attribution of authorship managed
by the European Copyleft Office.
Network rules and governance. The key role of network fluidity and density for the Learning-
intensive Society Learning Spaces is to maintain and extend its neutrality. A way of maintaining the
accessibility of digital resources might be to authorize the Internet Engineering Task Force (IETF) to
implement by its running code principles a set of user objectives that sustains net neutrality.
Additionally, wireless gigabit connectivity should be available at little cost everywhere in Europe.
Major milestones: By 2010 Europe succeeds with net neutrality as a governance principle. In 2015
wireless gigabit connectivity for free covers all of Europe.
Searching and the meaningful web. Open learning in the Learning-intensive Society Learning
Spaces requires universal systems for indexing, semantic referencing, archiving, and privacy. Europe
should therefore support and promote open standards for indexing and searching the smart web.
Major milestones: Europe negotiates and establishes a universal standard for greater web
transparency and searchability by 2010. By 2015 universal indexing and the full implementation of a
multiple-source meaning of bottom-up key words should be common practice throughout Europe.
The end of compulsory schooling. Announcing that compulsory schooling will end for all children
by 2020 provides a powerful catalyst for the development of alternative institutions that are more
effective and efficient at accomplishing the five primary functions of industrial-era school systems:
custody, cognition, behaviour, socialisation and screening. Major milestones: By 2015 half of high
school students have opted out of the compulsory system. By 2020 the old classroom school is a
historical vestige.
A European Think Tank for Learning Spaces. The potential for the development of new learning
spaces merits a dedicated Think Tank for Europe. This European agency would serve as a research,
networking and consolidation hub for the weak signals and experiments related to LS throughout
Europe and in the world. Major milestone: ELSA – European Learning Spaces Agency is established
in 2010.
1 Why think about the future of learning spaces now?
Few policy themes are more pervasive than learning. Learning is considered a prerequisite for
addressing a vast range of policy challenges, from achieving higher rates of innovation and enhanced
competitiveness to resolving the tensions of multiculturalism and improving people’s health. Yet the
ubiquity of learning as a solution to so many woes is also a source of ambiguity, even confusion.
What is the purpose of learning? Are there best ways to learn? When and where do we learn? Are
people motivated to learn? Are they able? What is the impact of learning on the economy and
society?
These questions originate from the fact that learning is simultaneously individual and collective, a
means and an end, active and reflective. They reflect that learning is also defined by its context: the
why, how, when, and where of acquiring knowledge at a particular point in time. Since learning
contexts differ and change with society, efforts to address these questions and propose policy
solutions have to avoid both, a too narrow focus on specialized fields, and, equally limiting, a too
broad perspective encompassing everything and nothing.2
“Learning Spaces” (LS) is the term used in a report published in 2006 by the Institute for Prospective
Technological Studies,3 “as a way to embrace a different view of future learning” (p. 33). A
description of what LS are and how they operate on a day to day basis in Europe in 2020 requires a
description of the economic, social and governance context that “sets the stage” – the context for
learning. In practical terms, this means that the LS scenario set developed for this report must be
nested within a scenario of the broader European society of 2020.
The concept of “learning spaces” can encompass the multi-faceted reality of learning – particularly
for analytical and policy purposes. LS are crossroads. LS include all of the different strands, both
tangible and intangible, that constitute the nexus that is learning. This combination of terms –
learning and spaces – may seem curious; the word “spaces” is usually understood as referring to
physical places – a specific terrain or volume defined by the parameters of distance - and learning is
quite often taken to be an individual practice, a personal activity. Why should the word “learning” be
associated with the word “spaces”? While learning has traditionally been assigned to specific spaces
such as classrooms, research labs, workplaces, and homes, the reality of "space" is currently
changing. Not only are ideas, people, and things more mobile, but time and place constraints for
connectivity can be de-linked in contexts that have become 24/7 and asynchronous.
Associating the words 'learning' and 'spaces' to form a composite term4 is symptomatic; shifts in
language are often signals of new phenomena, even of patterns – sometimes systemic patterns, that
are not yet evident to the biased eye of common sense or the entrenched categories of researchers.
Although it is difficult to know which words or phrases to attach to new phenomena, the appearance
2 Cf. Gavigan, 1999.
3 N.B., the term “learning spaces” has been in use for some time with respect to the architecture of buildings, like universities and
schools, which are intended to provide a physical place for learning. The development of a broader, ICT-enabled meaning for the
term “learning spaces” was put forward in Punie & Cabrero, 2006 & Punie 2007. New competences and skills related to new
learning spaces are discussed in Punie & Ala-Mutka, 2007.
4 Lefebvre, 1991.
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of such new ideas or views can be thought of as a clue, a signal5 that something may be happening.
That is the starting point for this report and the rationale for using a term like Learning Spaces (LS).
The premise for this report is that changes taking place in the world around us today signal the
emergence of a new context for learning and hence policy makers need to think about what this
means for why and how learning is organized.
The hypothesis that the context for learning is changing in potentially systemic ways is supported by
many facts or observations from our present surroundings. The term “learning spaces” can be a
useful lens or meta-framing6 device for detecting and focusing on these facts in order to tell a story
about what is happening to learning. Since every story about the present contains an anticipatory
element7, searching for the meaning of learning spaces is a way to think about the future of learning.
This report will render more explicit the anticipatory part of the story of learning spaces by
imagining a possible future for learning spaces in Europe in 2020. The story is confined to imagining
and does not address issues of probability, likelihood, or desirability.
The report is organized into seven chapters and three annexes. Chapter 2 examines current
phenomena to look for signals or clues that the context for learning is changing and therefore that
learning spaces might be both different and important in the future. Chapter 3 lays out the
methodology employed to imagine the future of learning. Chapters 4, 5 and 6 form the core of the
imaginary exercise on the future of learning. In chapter 4 the vision of Europe in 2020 as a Learning-
intensive Society (LIS) with Learning Spaces (LS) at its centre is developed and spelled out. Chapter
5 gives a detailed account of the fundamental characteristics of Learning Spaces in the LIS. Chapter
6 assesses basic requirements and different possible enabling conditions for LIS-LS, the “how-to”
scenarios, by contrasting (“backcasting”) LIS-LS to the present. Chapter 7 closes with suggestions
for policy.
5 Such signals may be weak (like virtual realities that are not evident to many) or strong (like cell phone usage that is obvious to
most people) without revealing its meaning or role (again weak or strong) in the way the potential of the present is actualised in
people’s anticipatory assumptions.
6 For a perceptive and provocative discussion of the term “lens” with respect to foresight, see Aaltonen, 2006, and Rossel, 2007.
7 Adam, 2004.
2 Signs of a changing context for learning
Currently, the conventional way of discussing the phenomena that lead people to believe or expect
something about the future is to talk of trends and drivers. Trends are phenomena that have been
detected (measured) in the past, exhibit a specific pattern (usually increasing or decreasing at a
particular rate), and can be extrapolated into the future. Drivers, as the word suggests, are agents or
agencies that both exert a force (pushing on the accelerator or the brake) and a direction (steering
through the choices they make). Both terms have a reassuring familiarity and, if only implicit, offer a
sense of legitimacy by using the language of what might be called “predictive science” (forecasting).
Although the term trend is typically used quite loosely, it nevertheless connotes a foundation of
expert empirical analysis. The term ‘drivers’ also conveys the impression of deeper causal analysis,
even of the kinds of theory and modelling that are requisite for social science.
Assessing the nature of change is a complicated task. It is crucial to attempt to distinguish between
those changes that are adaptive, part of the resilience of an existing system, and those that may signal
the emergence of new, distinct systems. This report examines a wide range of phenomena – many of
which are technically neither trends nor causal factors – but may nevertheless be indicative of the
kinds of changes that inspire imagining a changed context for learning in Europe in 2020. What is
crucial when looking at these phenomena – a few of which might legitimately be labelled trends and
drivers – is to attempt to distinguish between those changes that are adaptive, part of the resilience of
an existing system, and those that may signal the emergence of new, distinct systems.
For instance, there is no reason to assume that a change that is part of an adaptive process (intra-
systemic), that for all appearances looks initially like a reform meant to preserve a system, does not
end up eventually playing a role in its demise.8 There are also phenomena that seem to be outside
existing systems (extra-systemic) but on closer inspection or, more likely, with the insight of
hindsight, seem to be dependent and/or defined by an existing system(s). This kind of symbiosis, that
often combines aspects of competition and cooperation, is characteristic of changes in hyper-
complex social systems. An example of this kind of compositional change is the historic shift from
agricultural to industrial society. Farming does not disappear entirely and remains essential for
human subsistence, but it is no longer the dominant component of the whole social picture.
Phenomena, be they trends, drivers, acts/non-acts or events/non-events (since when it comes to the
evolution of a system the things that do not happen may be as important as those that do), can also
belong to more than one category of change. Furthermore, there is overlap and interaction that means
that there can be change in change. How the future will actually play out is uncertain. The future
does not yet exist. However, what does exist is anticipation, in the present, and as one of the key
determinants of choice (although not necessarily of actual outcomes). Therefore, what is practical
and serves as the starting point for this report is an exploration of present phenomena and past
experiences in order to detect and explore signs of a changing context for learning. These signals
provide the inspiration for imagining a social order (in Chapter 4) where the aims and methods of
learning are different from today. The present is thus used as a springboard for imagining
(anticipating) a distinctly different future.
8 Carr. 1951. A fascinating example discussed by the historian E.H. Carr is the case of Czarist Russia where the imposition of highly
repressive restrictions on democracy contributed, in his view, to the creation of three generations of ardent revolutionaries.
However, extending Carr’s argument somewhat, even though the Czars did not sustain their position in the Russian system, it
could be argued that they did succeed in staving off democracy well into the 21st century and thereby somehow their choices did
contribute to the resilience of an autocratic social order.
1
The survey of relevant phenomena in this section examines the changes taking place in the world
today at three different levels – the aggregate macro, the institutional meso, and the individual agent
micro.9 Distinguishing these three levels helps to reveal signs that the present contains the possibility
that the context for learning may change. It is then, on the basis of this evidence, that the following
sections of the report imagine a distinctive anticipatory story – one that provides a non-linear (i.e.
change in the conditions of change – non-ergodic) context for learning spaces in Europe in 2020.
2.1 Macro-level trends and drivers
The challenge of assessing aggregate level changes is finding the appropriate indicators. First of all
just adding up changes in the sub-components can lead to serious errors when the whole is more than
the sum of its parts. A further complication is that general changes in societal context may actually
arise from extra-systemic developments, phenomena that are outside the old way of defining and
measuring aggregates. As are result, accounting frameworks that are embedded in the past may
actually hide the key indicators of macro-level change. Thus, it is not a straightforward task to detect
and describe the aggregate level phenomena that may signal significant changes in the context for
learning.
Three society-wide phenomena are discussed here; the emergence of new skills and competences,
demographic changes, and globalization. Current developments in all three areas indicate that the
context for learning is changing at a macro level.
2.1.1 New skills and competences
In considering the nature of macro level changes in the mix of skills in society it is important to
distinguish changes in quantity and quality as well as changes that are intra- and extra-systemic.
Starting with the most familiar, it is worth noting that from a quantitative, intra-systemic perspective,
the churning of careers, and the demand it generates for the acquisition of “new” skills, does not
necessarily alter the context for learning. It certainly puts pressure on existing suppliers and ways of
producing sufficient skill levels, but in most situations this kind of churning is well within the remit
of existing learning systems. And, for the most part over the last few decades, such reallocation has
been accompanied by efforts to reinforce and improve the long-standing and highly successful
contexts for learning of the past – the education and training systems of the industrial era.
This is not to call into question the readily available signs of macro-level changes in the skills and
competences of a society based on indicators that categorize what people know. These familiar signs
of change can be seen in the following:
! The reallocation of activities occurring due to shifts in the international division of labour as
firms and jobs move around the world; a reallocation of employment and jobs arising from
competitive and technological threats and opportunities, global sourcing and automation. All
of these changes are creating new hierarchies of work, the need for new skills and
competences, and processes of continuous updating of skills and knowledge.10
9 As developed also in the IPTS Learning Spaces Report: Punie & Cabrera, 2006.
10 Gartell et. al., 2007.
2
! An increased focus on collaboration, cooperation and partnerships across departments,
cultures, companies, sectors and borders is leading to a focus on the acquisition of new skills
or improving existing ones in areas like: interpersonal communication, teamwork, project
management, contract and terms negotiation, conflict and risk management, languages and
interpersonal skills.11
! The advances taking place in the sophistication, the ease-of-use and diffusion of new tools,
particularly the maturing IT field12 is generating a demand for new skills.
All these factors generate both a push and pull for learning related to new products, new networks,
and new processes.13
All European countries are, to varying degrees, facing these traditional macro-level learning
challenges.14 New skills and competences related to changes in specialisation, collaboration, and
improved tools, continue to emerge in the public as well as in the private sector. From a macro-level
perspective, this ongoing process of skill reallocation and the development of new competences
signal potentially disruptive changes in the context of learning.15 But when does quantitative change
demand systemic change? Can qualitative changes be accommodated by existing systems? Are extra-
systemic developments outside the up-until-now dominant system beginning to replace the old ways
of doing things?
These are all difficult questions, pertinent to the challenge of ascertaining if the context for learning
is changing in ways indicative of the emergence of a new system of learning spaces. The answers can
only be speculative. On the surface, the macro-level changes taking place in skill mixes signal a need
for qualitative and quantitative supply-side responses.16 Ongoing intra-systemic reform to adapt to
changing demand remains and the need for greater efficiency in the delivery of conventional
educational services remains high on government agendas.
However, outside the beam of existing skill indicators there are also signs of change, ones that may
be more extra-systemic or discontinuous. Plumbers, welders, school teachers, mentors, coaches, care-
givers, parents, friends, teams, and competitors, all know things related to what they do. This know-
how is the “real” data set upon which macro-level indicators are based. There are both official and
unofficial (lived) signs that deeper changes are afoot, even though what is actually measured is
mostly based on the know-how categories that are largely related to the industrial past. In particular,
there are signs in the present that a greater number and range of skills are needed to live well in a
diverse and ambiguous society.17 Such changes may be signalling a macro-level shift in the learning
context of every-day life.18, 19
11 Cairncross, 2001.
12 McFarlan and Nolan,2003.
13 For a wider illustration of these types of change see EMCC sector futures studies
(http://www.eurofound.europa.eu/emcc/sector_futures.htm); See also Fichman, 2000.
14 European Commission, 2007a.
15 See also, for activities on eSkills and EU work on eSkills: http://ec.europa.eu/enterprise/ict/policy/ict-skills.htm
16 Gardner, 1983 and 1993.
17 Bauman, 2004 and 2006.
18 The term “every-day life” is used throughout this report. Here the term is refers to a direct relationship, the one-to-one mapping of
decisions, including those related to learning, to people’s daily acts – from the humdrum to the transformative. There is certainly
an extensive literature spanning a range of fields that addresses the multiple dimensions of the construction of every-day life, a
fascinating and pertinent topic that, however, cannot be addressed directly given the constraints of this report.
3
2.1.2 Demographic changes
Macro-level changes in both the demographic and social composition of European societies are well-
studied phenomena.20 The typical story is one that focuses on a future where the average age in many
European countries continues to climb, the rate of population growth slows, and the risks of
entrenched or more polarised stratification increases. The wildcard is usually migration, legal and
illegal, from within and outside the European Union.21 Two of the most discussed general
implications of aging and migration are, on the one hand, an increase in the demand for skills and
skills training along the standard industrial era categories of know-how and, on the other hand, a
relative reallocation of time and resources to questions of health, social welfare, etc. (quality of life).
When it comes to skills and education the social side of the story regularly focuses on exclusion and
the role of training in overcoming it. Thus, many factors are expected to account for the training
boom related to skill shortages, including a relatively higher rate of retirements, lower rates of young
people entering the labour market, reallocation of the demand for labour towards services that cater
to an older population, the needs of immigrants for specific work related skills, and the general
learning costs associated with widespread re-skilling.
Other demographic factors, such as the changing population distribution between urban and rural
areas22 and differences in the capacity of specific population sub-groups to engage in or even access
training, are also expected by many to exert pressure on current learning infrastructures.
Multiculturalism or the changes in women’s role in society also provoke a demand for training.23
Extrapolating from current phenomena like the high cost of maintaining traditional schooling in
sparsely populated rural areas or ensuring quality schooling in deprived urban areas, the typical view
is that skill distributions maybe very uneven. This, in turn, is expected to generate pressure for
reform, not only in the training sector, but also in the business, social services, and cultural sectors.24
One line of speculation is that without sufficient or successful reform, segregation is likely to
reinforce the division of society into learning-poor and learning-rich segments and places. In many
medium-sized and large European cities this is already the case, with immigrants concentrated in low
quality schools in specific parts of the city. Another line of speculation, also rooted in observations
of present day phenomena, is that there will continue to be a shift away from the one-size-fits-all
solutions of the mass-production era towards “personalization” of education. Throughout Europe,
reform efforts are underway aimed at improving the capacity of industrial era organizations, like
schools and universities steeped in the practices of scale economies, to tailor services to a population
that is more differentiated in its origins and, perhaps more importantly, in its aspirations.25
Similarly, seen from a European-wide macro perspective, the strains on the existing systems for the
provision of services aimed at ensuring the health and well-being of European populations may
signal both conventional and unconventional changes in the context for learning. On the
19 See Rychen and Salganik, 2003, for an attempt to define the broader set of competences (OECD DeSeCO project)
20 Fotakis, 2003; Coomans, 2005; and the SSO (European Observatory on Demography and the Social Situation)
21 EFMN
22 United Nations Population Fund, 2007
23 Doomernik, 2001; Batlle, 2007; Pemint
24 Eurydice
25 Department for Constitutional Affairs, 2007
4
conventional side, in Europe and the rest of the world, increases26 in chronic health disorders are
generating a demand for learning. So, too, are other health risk factors such as stress, physical
inactivity, tobacco, unhealthy diets, and alcohol consumption. Such direct demands on existing
health services alter the context for conventional learning supply in a number of ways. For instance,
addressing the growing problems of chronic diseases increases the demand for education and
learning among healthcare professionals, advisors, and citizens in general.27 The diversity of the
demand for training and research, including by people suffering from chronic diseases, is pushing
innovation by both users and suppliers.
Less conventional signals of change such as policies aimed at breaking down institutional borders
and practices through inter systemic approaches that “join-up” education, research, and health care,
may be indicative of a more significant transformation in the context for learning. One weak signal
could be the degree of difficulty encountered in all OECD countries as well as throughout Europe in
getting beyond existing practices. Here there are signs of a mismatch between macro-level
phenomena and what policies within existing frameworks can achieve. This could be a signal of the
emergence of a new context for learning, one that reflects a redefinition of what it means to be
healthy and live a “high-quality” life.
2.1.3 Globalization
Another major macro-level phenomenon, perhaps the most cited of all today, is globalization.
Despite the many often inconsistent and a-historical definitions, there is abundant evidence that the
international nature of much trade and business development creates the need for new skills and
knowledge, but in many instances along with conventional industry era categories of know-how.28
As already noted, the reallocation that is part of such internationalization has led to job destruction
and also to new jobs being created. This requires a flexible workforce that is capable of un-learning
outdated competences and learning new ones (for instance the closure of a meat processing company
in Denmark led to several workers being retrained as social care workers29 ).
At an aggregate level, the churning within mainstream sectors and existing occupations certainly puts
pressure on both the demand and supply for skills. However, beyond the conventional processes of
economic specialization and the shift towards services, long-standing attributes of Europe’s mature
industrial societies, globalization may also increase the potential for changes in the macro-level
context for learning in three distinctive ways.
One is the coincidence with a breakdown in the way “products” are conceived, produced, and
consumed. This phenomenon30 is known variously as “co-production”, “co-design” or pro-sumption.
When combined with open, relatively low-cost international networking – the flow of both tangibles
and intangibles – the potential for change in the context for learning could be significant.
Cumulatively, this way of producing alters the location of conceptual knowledge in the value chain;
more people are coming up with their own ideas and making their own decisions in which design,
learning, and use are closely connected, thereby altering the learning arena. As a result learning
processes, also called “research and development”, “trial and error” or “entrepreneurial leadership” –
26 World Health Organization, 2005
27 Cline & Haynes, 2001.
28 Florida, 2005, and Castells, 1996.
29 EIROnline (2004)
30 Von Hippel, Eric (2005); Prahalad and Ramaswamy, 2004; Miller and Bentley, 2002.
5
depending on the institutional context (government, university, company, start-up, street), could be
facilitated or enhanced by greater global openness (transparency, low barriers) and networking (ease
of community creation, ease of flows, and high density of connections).
A second similar type of transformation in the context for learning that could also be enhanced by
“globalization” is related to the process of identity formation in society. Here again, learning is
generated by the actions taken by individuals and groups in relation to the communities that surround
and touch them. The “smaller world” created by the speed and ease with which everything flows may
be a key factor in providing the diversity and inspiration necessary for such heterogeneous learning
needs and processes to be satisfying for both individuals and communities.31 All of the micro level
choices, which on an aggregate level go beyond the perimeters of the local, could alter the way
societies as a whole (macro-level) forge the relationship between identity and community. Certain
global phenomena like the web, migration, tourism, trade, pandemics, climate change, etc. offer non-
local learning in response to the basic identity questions of “who am I?” and “which communities am
I part of?”
A third macro-level change might emerge from an overall increase in heterogeneity or “difference”.
Although there are signs of world-wide homogenization or a reduction in differences, many
observers detect fragmentation beneath the surface of similarity as old imposed identities lose
meaning and power while the capacity to seek and engage in networked based community building
grows. Such greater diversity may indicate a changing context for learning. Overall, at the macro-
level there is more “difference” and this highly differentiated context is more propitious to learning
than one that is uniform. In this sense globalization may alter the macro-level context for learning by
augmenting the diversity within which learning occurs. As more and more micro-level learning plays
out on the diversity of a world stage, the cumulative result has the potential to alter both what and
how learning happens.
2.1.4 Macro-level observations
Do these three sets of macro-level changes discussed above: the new skills that are solicited, the new
roles for a given age and place when compared to the past, and the scale of the stage on which people
play, really add up to a new context for learning? Is it justified to argue that at a cumulative level the
impact of these changes on the context for learning points towards a discontinuity in the nature of
learning spaces? Or, is this just another example of “hubris of the now”, that fairly universal human
inclination to think that one’s own brief moment of consciousness is in some way remarkable, that
leads to the claim that what is happening now is really different from the past?
There is no definitive answer to this question. Globalization, defined as an open and networked
planet, marked by large and unimpeded flows of goods, ideas, and people, is still a relative concept.
As many commentators point out, the world is not flat, at least not yet.32 Yet de-territorialization and
the emergence of non-spatially delimited communities are beginning to pose problems for territorial
based policy - even for a territory as broad and multifaceted as Europe. Current phenomena are
provoking questions, many of which have been posed before,33 that cumulatively may signal not
31 Part of this hypothesis relates to the question of the relationship between a growing diversity of learning processes and the
“resources” necessary to really satisfy heterogeneous learning. It is not at all clear that the local cannot offer such richness of
experience, nor that the diversity of the local is inadequate to the banal creativity that is inherent to most learning.
32 Ghemawat, 2007
33 Illich, 1971, 1976.
6
only a departure from the past but a moment when the inter-action of changes at different levels and
from different sources creates the conditions for imagining a different future. Expressed in more
conventional terms, it is a commonly held view today that many macro-level “drivers and trends” are
reinforcing each other and generating a strong impact on the context for learning.
2.2 Meso-level trends and drivers
Institutions are always adapting, reforming, changing leadership, expanding, contracting, conquering
new territory, or dying. The challenge here is to determine what kind of change is occurring and what
the change reveals about the potential for change in the future context for learning. Often,
generalizations do not hold across types of institutions and different places. For instance, changes to
the family as an “institution” often cannot be understood in the same terms as changes to the “firm”
or “enterprise”, and changes taking place in institutions of collective choice (legislatures, state
executives, political parties) often differ from one location to another.
The list of current meso-level changes is a long one, with many variations throughout Europe,
including at the level of Europe as a whole.34 The temptation, naturally, is to focus on the
institutional reforms and transformations occurring in the broad education sector and within firms,
since these have traditionally been the two pre-eminent locations for “official” learning – the
industrial era’s dominant learning spaces. Certainly, the changes taking place in the education and
training systems and in the human resource development systems are important. However, there is
another way of thinking about these changes that hints at two weak signals of discontinuous change.
One is the shifting nature of the authority wielded by traditional sources of control and choice and
the implications this has for learning. The other is the emergent “institutions” of Web 2.035 that also
seem to open up potentially new horizons for learning in many different forms and for many
different purposes.
2.2.1 Formal versus informal learning36
Perhaps the most noteworthy meso-level signals of a new emerging context for learning have to do
with what might be called the “institutional footprint” or the power/authority and coverage exercised
by the formal systems of classroom schooling, university degrees, corporate human resource
development, R&D, etc. Although existing indicators of institutional status do not offer a
straightforward signal, there are current phenomena from a range of different perspectives that
suggest that the relative coverage of the formal learning systems seems to be shrinking. Informal
learning is regaining pride of place in use and recognition outside the credentialist systems of the
industrial era.37 , 38
34 Tomusk, 2007.
35 http://en.wikipedia.org/wiki/Web_2
36 Formal learning is typically provided by an education or training institution and leads to certification. It is intentional from the
learner's perspective. Non-Formal learning is provided by any organised, structured and sustained educational activities outside
formal education. It is intentional from the learner's perspective, but typically does not lead to certification. Informal Learning is
learning that results from daily life activities related to work, family or leisure. It does not lead to certification and in most cases, it
is non-intentional.
37 See also OECD country reports (OECD 2007c, forthcoming) on the recognition of informal and non-formal learning. Korea, for
example, has already developed a competence credit bank system.
38 Citizendium; Sanger, 2007.
7
This does not mean that existing systems are not growing, since there can be little doubt that on the
basis of conventional indicators such as spending on education be it in formal educational institutions
or within firms engaged in “professional development” that the business of training is booming. A
similar story of ascendance might be told by looking at the energy being devoted to reform of the
education sector as governments proclaim the importance of education for innovation and
competitiveness.
However, outside the spotlight of traditional data sources there are changes related to the kind of
knowledge being produced and the way it is produced and used.39 Such changes have been addressed
in part by the literature on “national innovation systems,”40 or the “creative class,”41 or the
“democratization of innovation”.42 Equally noteworthy phenomena that escape the existing
certification and ownership boundaries of the formal education and research institutions can be found
in the emergent fields of open source knowledge and the spontaneous communities of practice that
are part of the social networking movement that has recently been popularized under the moniker
Web 2.0.
These phenomena are still only partially developed and the theoretical models and empirical metrics
are only starting to be articulated.43 As a result the signals are still weak, difficult to detect and/or
difficult to interpret. The meta-frames needed to help measure the changes and determine the
meaning – continuity or discontinuity or both – are only emerging. Indeed, it is precisely one of the
functions of the Learning-intensive Society scenario described in the following chapters to assist
with the detection and interpretation of the meaning for learning spaces in Europe of phenomena in
the world today.
Beneath the surface of the facts and the lists of trends and drivers, there is a change in the outlook on
life which many people in Europe today subscribe to:
! People are less impressed and restricted by the perception and legitimacy of the external
authority of father, teacher, employer, and government;
! People are less homogeneous across a wide range of categories – from lifestyles and video
windows on the world to next door neighbours and products on the kitchen table;
! People are less certain with respect to belief systems, role models, work patterns and the basic
attributes of identity; and, in many ways,
! People are less autonomous as the reality of inter-dependency and the necessity of networking
impose an awareness of mutual responsibility.
If these phenomena are present in the Europe of today, then it is the reality of freedom, ambiguity,
diversity, inter-dependence, and responsibility, which is expanding the meaningful and useful realm
of knowledge and learning. Looked at from the meso-level of institutions like the family, the school,
39 Akrich and Miller, 2006.
40 http://www.druid.dk/ and also Lundvall, 1992.
41 Florida, 2005
42 Von Hippel, 2005. Also http://web.mit.edu/evhippel/www/
43 Benkler, 2006.
8
the firm, the state, this enlargement of the need and desire to know is, almost by definition,
happening outside or with little reference to the old institutional boundaries.
One of the strongest symptomatic indicators of the changing boundaries and challenges to the
historical predominance of existing institutions is that these very same institutions are changing,
reacting and adapting – sometimes willingly, sometimes not.
! The family, as the fundamental social institution, is taking on all sorts of new configurations
and its members are assuming new, often unfamiliar and open-ended roles. The family’s place
and relationships in society are being renegotiated, as legal, fiscal and everyday services are
reshaped to take on the greater diversity. Intergenerational and cross-lifestyle conflicts create
learning opportunities that do not always resolve easily. The lack of precedents, the obligation
to explore and construct new roles and models, also means that the required learning-by-doing
can be both painful and highly rewarding.
! The old learning spaces, dominated by the immensely successful organizations of the industrial
era44 like schools and universities, are struggling to maintain authority and control over the
definition and certification of knowledge while at the same time remaining true to the stated
mandate of helping to equip people and society for a life where learning is much more
heterogeneous and heterarchical.
! Firms, trying to increase productivity in a flexible world invest in knowledge management and
more intensive human resource development. However, they are caught by a number of
intractable dilemmas, some of which are rooted in the privacy and mobility of “human capital”,
and some of which stem from easy reproducibility in the digital sphere, the power of open
source, and the large externalities generated by the digital commons.
! Institutions of collective choice – from municipalities and nations to NGOs and international
organizations of all kinds – are having difficulty being effective in a context where
bureaucratic and lowest-common-denominator mass-scale solutions no longer fit the needs of
diverse and self-directed populations. Indeed, there may be an uncomfortable, potentially
debilitating incompatibility between what John Kay calls the disciplined pluralism45 of
experimentation and the bureaucratic managerial chain of command that punishes failure.
From today’s vantage point it is impossible to say which of the previously successful institutions will
prove resilient and why. Many of these institutions are in the midst of self-declared ambitious
reforms, presumably because there is a general consensus that conditions have already changed and
will continue to do so. In addition, a variety of signals point towards a diffusion of authority and the
decentralization of meaningful and effective action as scale-based, bureaucratic solutions give way to
more local, information-rich, and just-in-time choices.
This means, in the practical terms of what people do and decide, that continuous and diversified
experimentation is the basis for an increase in both quantity and quality of learning. The quantity of
learning is higher because people are persistently, throughout their lifetimes and day-in and day-out,
challenged to experiment as they willingly or not co-produce the world that is meaningful to them.46
44 Miller, 2007b.
45 Kay, 2006.
46 Kirkeby, 2007.
9
With respect to the quality of learning the greater intensity arises from an equally continuous
confrontation with ambiguity and uncertainty that, all other things being equal, generates experiences
that on a cumulative basis deepen a person’s knowledge.
Detecting this return to the importance of wisdom may be difficult since measuring the quality of
learning has long been subject to hierarchically based assessment systems of a largely technocratic
bent. This is not to deny the importance of scientific judgement and inter-subjective assessment.
However, what may be distinctive about the learning associated with present phenomena is that it
essentially escapes from such judgemental hierarchies. The way people find meaning in their lives,
be it water skiing or gardening, blogging or paid work, is up to them and falls outside the high-low,
better-worse scales of the pyramids of hierarchical judgment.47
No one else can judge or discover your “Heart Song” as Miss Viola explains to her class of young
penguins in the film Happy Feet, quoted at the outset of this report. This means that as long as people
exercise their freedoms and responsibilities within the bounds of the basic rules of the society, then
the way they solve the “problem” of meaning, of co-creating their lives is their concern (hermits –
the illusory monad individual – aside). By the same token, so too is the “quality” of the learning that
gets them to their identity rooted in “banal creativity”48 – each person has their own tastes and ways
of refining those tastes. However, it is precisely the subjective nature of this “banal creativity” that
puts such a large share of learning outside the existing institutional perimeters. Today’s predominant
institutions are more than operationally dependent on the use of hierarchies as a means to coordinate
action, such institutions are the embodiment and carriers of hierarchy throughout society through
status and imprinting.49 As a result non-hierarchical (heterarchical) learning fails to fit within the
logic that sustains such institutions.
There is no point in trying to estimate the extent to which existing institutions with specific
historically established aims, rules, metrics, and organizational methods can perceive and adapt in
order to integrate or co-exist with emergent phenomena. Nor if such adaptation will or will not
contribute either to the resilience of the existing system or the emergent ones. Quite often, the old
systems have difficulty even detecting new phenomena. Imagining alternative systemic situations is
one way of trying to become aware of these gaps in knowing, to understand how the working
assumptions used by decision makers actually narrow choice.
2.2.2 Educational reform – how far can it go?50
Changes at the meso-level can be seen throughout Europe as education systems are being reformed
to respond better to the knowledge society. These often high-profile reforms of primary, secondary
and tertiary systems reflect the widespread recognition of the need for extended learning networks
that go beyond the borders of single institutions and offer the possibility of recognizing diversity,
encouraging the mobilization of social capital, and enabling powerful collaborative and relevant
learning experiences.51 For learners of age 18 and above, much of the formal education that is taking
place is still mainly defined by industry needs.52
47 Miller, 2006a.
48 Miller and Bentley, 2002.
49 Espinosa, Harnden, and Walker, 2007.
50 OECD, 2007b.
51 http://www.eun.org/portal/index.htm
52 Townsend, 2007
10
Reforms within education institutions are, largely within the confines of the industrial logic that
binds the existing systems, moving towards empowering learners, enabling creativity and self-
determination as more firms are calling for more flexible and self-motivated workers down to shop
floor level.53 , 54 In some of the most innovative and successful flexible learning institutions (e.g.
NKI55 in Norway, Open University56 in the UK and Phoenix Online57 in the USA) new learning
agents are emerging representing new roles, processes, and relationships in the learning economy.
They create new career paths and greater specialization in education – content experts, learning
coaches, network navigators, classroom managers, and cognitive specialists - corresponding to the
types of specialization that occur across economic sectors. In some cases, these frontrunners begin to
influence mainstream education institutions as they try to define next steps.58
Seen from a meso-level these reform efforts, as already noted, are symptomatic of institutional
change, although in many places “reform fatigue” seems to be setting in.59 Can the education
institutions of the industrial era transform sufficiently to become part of another learning context? Is
it desirable or necessary? Will a loss of pride of place, of power, of share in the overall learning pie
lead to internecine warfare that marginalizes the old systems or to renewed efforts to transform into
post-industrial institutions or simply to an approach that stresses coexistence and synergy? Will the
education establishment do itself in through bad management or internal resistance to reforms that
inhibit adaptation? Yet again, there is no way to know. What is doable is to imagine, as in the
scenarios presented in this report, different outcomes in order to help reveal the assumptions that
shape the decisions being made today.
2.2.3 Workplace learning – formalizing informality?
Employee communities of practice are predominant enablers of learning in many workplaces.60 In
many organizations, formal and non-formal learning co-exist, though it is a standing discussion that
much of the formal training does not have the intended impact on learning and competence
development.61 Lack of a connection between strategy and the human resources available may be
one side of the coin; notions of training offer and training supply and skills gaps as the dominant way
of talking about workforce learning may be another. As long as training is supply-driven and, as long
as employers and business managers keep buying it, the training supply business is not likely to
change. In certain firms, particularly SMEs, employees are motivated to find other informal ways of
learning what they need to know to do their jobs well. The introduction of social software62 can
support employees in their search for relevant knowledge and workable solutions. As task and job
responsibility is channelled down to teams and individual workers, more and more learning choices
are being made by individuals.
53 Hargreaves, 2003
54 Kirkeby, 2007.
55 http://www.nki.no/index.xsql
56 http://openlearn.open.ac.uk/
57 http://college.us.com/Aff/?partner=1088&source=1014&key=phoenixonline
58 The Knowledgeworks Foundation, 2006
59 Andersen, 2007; Mandelson, 2005.
60 Kurtz and Snowdon, 2003.
61 Lassen & Plougmann, 2005.
62 Tapscott and Williams, 2007.
11
More generally, despite the fact that the institutional or meso-level contours of Web2.0 and social
software are not yet clear, they are already signs of important developments in where, when, how,
and why learning takes place. Web2.0, social software, wikis, and tagging through folksonomies,
empower learners to create content, discover each other, and share content and experiences.
Blogging and multimedia versions of blogging have undergone an immense growth both in general
and specifically in relation to learning activities63 . Although the boundaries that distinguish formal,
informal and non-formal learning and the role of education institutions and the business community
have not formed any definitive patterns, there is already enough activity to signal new meso-level
potential. The notion of “formalizing informality” is meant to suggest, once again, that the old
hierarchies and power centres may be ceding terrain to more heterarchical reference systems and, if
not a direct diffusion of power, a greater dispersion and turnover of arbiters, intermediaries, and
relevant actors.
2.2.4 Meso-level observations
Diversification of life and learning trajectories is generating a new learning terrain and potentially
new institutions, while at the same time challenging existing ones. As the boundaries of learning
change, so too do the positions and roles of institutions. Macro-level phenomena, already mentioned
above, such as globalization, demographic changes, or shifts in values, are currently transforming the
context for learning, albeit without determining any specific outcome for Europe in 2020. Nor is
there any clear verdict regarding the reform and adaptation of education systems in Europe. Few of
these reforms are occurring in the same way or at the same pace across countries and institution.64 In
thinking about the meso-level implications for imagining changes in the context for learning calls for
careful consideration of the way in which existing educational institutions do and do not change.
Looked at from the perspective of institutional adaptation some signs point towards a neglect of the
emerging terrain of informal learning.65 For instance, there appears to be reluctance towards
alternative means for establishing reputation or facilitating open source or new intellectual property
rights like Creative Commons. Still, changes in the overall institutional context for learning are not
only shaped by reactions and initiatives on the educational supply-side. Other institutions, both
existing ones and emergent ones play a role. In this regard enterprises, as one of the traditional
institutional sources and motivators of learning, may end up leading some of the changes related to
knowledge creation and acquisition. Many expect that the diversity of approaches for organizing
learning at the enterprise level could indicate real opportunities to experiment and to discover new
ways to support and facilitate knowledge sharing inside and outside companies. Such phenomena
may be amplified or accelerated by the learning occurring through the tools and communities of
social networking that many call Web 2.0.
2.3 Micro-level trends and drivers
What are the micro-level signals that a change in the context for learning may be emergent in Europe
today? Again this is not an easy question. Micro-level change is about what agents do – the
motivations, ideas, and relationships of many small decision making units such as individuals or
63 SPIRE project, 2007
64 European Commission, 2007b.
65 More recently the evolution of open source courseware and the issues of copyright (OECD/CERI) and the persistent lack of
structural uptake of recognition of formal and non-formal learning systems except for in a few countries such as Australia and
Canada have a direct bearing on the evolution outside the existing rules and institutions.
12
firms. Generalizations in this field are most often about specific behavioural patterns, typically
distinguished by age groups (marketing) or social strata (sociology) or types of firms (economics). In
this report, the primary unit of analysis is the individual learner and the micro-level changes that
matter here relate to changes in the capacity to learn.
The capacity to learn is multi-dimensional, with many determinants at any one time and place and
even more over time and in different circumstances. However the focus here at the micro-level is on
three “internal” aspects of why and how specific segments of the population learn: attitudes,
behaviour, and “cognitive capacity”. People at different moments in their lives may be more or less
open minded, curious, and ready to spend time and effort to understand and to share knowledge.
They may behave in ways that invite others to join them in experimenting and creating, or not. They
may have developed the cognitive capacity – the learning tools of conceptualization, analysis and
experimental practice, or not. Taken together these attitudes, behaviours, and skills make up the
micro-level capacity to learn.
Surveys of people’s attitudes focus largely on broad cultural values or the marketing of goods,
services and politics. Recent studies of learning behaviour have tended to concentrate on “brain
research”.66 There is no micro-level index of the capacity to learn, as defined here, that would
measure the extent to which people in a suburb of Paris, for instance, have a greater or lesser
capacity to learn than the people in say a small town in Finland. Existing standardized tests seek to
establish benchmarks for the performance of school systems and the population’s acquisition of basic
industrial era skills like reading, writing, and arithmetic, though there are attempts being made to
measure other types of skills such as learning to learn (by the EU) and in national systems such as
Finland. Yet a synthesis of these various fragments does not really offer the portrait of the micro-
level learning capacities of specific groups or even different individuals.67
2.3.1 Diversification of life: are learning cultures changing?
Significant changes are making life and learning trajectories more diverse and complex. In part, this
is related to previous observations regarding macro- and meso-level changes such as:
! changing age profiles of the population;
! shifting structures of employment;
! a more intimate mixing of the local and the global;
! households with diverse and more complex roles;
! social networks becoming more visible and more valued;
! professional identities and associated skills becoming more blurred in most occupations;
! people finding their values and learning in likeminded communities;
! work and learning moving into new public and private spaces; and
! experiences that become communities of practices and projects (immersive learning).
Within this changing context, there are also transformations at the level of people’s motivations, the
“psychological” or behavioural dimension of learning. In part, this might be called the “culture of
learning”. Many efforts to analyse and generalize about micro-level behavioural attributes rest on the
66 OECD, 2007a.
67 An excellent European source for attitudinal data is the European Social Survey, http://ess.nsd.uib.no which shows, for instance
that around 15% of people born in the 1930s did not identify with the statement that it is “important to do what you are told and
follow the rules”, while close to 30% of those born in the 1980s felt the same way. Are millenials less conformist, less obedient?
Maybe. (See Annex 7 for a chart extracted from the ESS data).
13
work done for marketing purposes that distinguishes categories based on age cohorts, such as the
“baby boomers” (1946-1964), “generation X” (1965-1981), the “millennials” (1982-2000) and the
tentatively entitled “generation I” for internet (2000-?).68 All four groups will be active learners in
the Europe of 2020.
Recalling E.H. Carr’s quote cited at the outset of this report about how anticipation shapes what
people see and how they explain it, careful attention needs to be paid to each group’s vision of the
future. Obviously the anticipatory assumptions used by different groups are shaped by their specific
history, the events and non-events, the imperatives and options that make up their day-to-day life and
form their view of the future. Equally important, although not as evident, is that these anticipatory
assumptions are constructed through different processes by different groups at different times, using
different building blocks (conceptualizations of time, causality, predictability, etc.).
The Baby Boomers: The boomers lived with the aftermath of the Great Depression and World War
2. They lived at the height of the Cold War. The boomer’s parents had won or lost, but succeeded in
reconstructing not just in terms of monetary wealth, but also in discovering and diffusing the
economic and social models that created both peace and fertile ground for amazing tools like the
telephone and television. The parents of the boomers were hard working, fully employed, carriers of
the myth of the nuclear family, disciplined by the competitive imperatives of the arms race,
chastened by the lingering taste of real war and the riveting fear of Armageddon, careful to not waste
because their memories touched times of hunger, and thankful for the escape from the horrors of the
first half of the 20th century. No wonder the boomers, in their overflowing numbers, first let loose in
the 60s and then went on to measure their own achievements with their parents’.69
Generation X:70 Now, as the vast majority of Gen Xers finally escape the interminable prolongation
of adolescence, a convenient excuse for denying young people their rights and freedoms, they live
with the handicap of growing up subject to influence of the paradoxical combination of bravado and
fear of failure that marks their boomer parents. Unlike the parents of the boomers, who could point to
achievements that were crystal clear since they were defined as the opposite of depression and war,
the boomers themselves seemed to have simply made a mess. Gen Xers grew up in a world with oil
shocks and economic cycles, celebrations of diversity and declining authority that generated little but
an excessively complicated and ambiguous day-to-day reality, more things but less reflective
meaning, antiquated codes of conduct based on fading cannons of obedience to boss and father,
working mothers that accepted getting men to wash the dishes as a feminist achievement, and
rampant technophobia with its flip side of techno panacea.
Millennials71 (sometimes also called Generation Y): The millennials, still mostly caught in the sweet
purgatory of extended adolescence, may be able to cut loose from the bonds that afflict Gen Xers.
Children of late child-rearing boomers and courageous Gen Xers, the millennials do not have much
to go on. They are often described as blithe or excessively care-free. They know of and shrug at the
reality of abundance and the hyperbole of catastrophe so rampant in a cacophonous world where the
fading of yesteryear’s mass-market success desperately screech for attention. Rejecting the queasy
uncertainties about future prospects of the Gen Xers, the millennials know that they will have to
68 The dates on this type of cohort analysis is approximate, for a discussion and further sources see: Wikipedia -
http://en.wikipedia.org/wiki/Generation_X
69 Howe and Strauss, 2000
70 Coupland, 1994.
71 Howe and Strauss, 2000.
14
figure it out themselves. In fact that is what the subliminal message really is about. No one has a clue
where we are going. Most anticipatory assumptions are off. Sure, into this void boomers are making
every effort to throw certainties about population aging, climate change, technological trends, and
the ascendance of Brazil, Russia, India and China, but so far not too many millennials are buying the
need to return to the planned economy and society of the mid 20th Century run by a global
government.
The experience of institutional schooling is common to all of these different generations. But, not
surprisingly, given the different anticipatory stances, the meaning of education across the generations
is not the same.
! The now disappearing Silent Generation (1925-1945), not wanting or needing to sing any
praises about their follies or achievements, still has an iconic view of school and its formative
role. This generation can feel and still believe in the stability and order of the industrial-era-
school as the anchor of a hierarchical system that marched into the future with sky scrapers,
jack boots and highways.
! Boomers are more doubtful but “rock ‘n roll” helped leave a rosy feel about school/university
and the solidarities and counter-culture it nurtured. For boomers education worked; indeed it
remains one of the last bastions of clarity of purpose, idealism, and order. That is why they
are such vociferous critics of what they see as the weaker school of today and such ardent
champions of school reform. They have been unsuccessfully championing life-long learning
for almost forty years now. Today more than ever they believe in education as a cure for all
ailments and the only hope for the future, given their own inability to figure out what is going
on. Extrapolating their experiences means that younger generations absolutely must be better
educated, because, for the boomers, that is the only way in which the next generation will
figure out what is going to happen in the future and then be able to save themselves by
planning accordingly.
! Gen Xers cannot find any really meaningful guidance from their parents’ meek refuge in
outmoded and no longer credible certainties that book learning, test scores, and “iron rice
bowl” career paths will save the day. But at the same time they do not seem to have the
wherewithal to escape the mindsets that come with the still dominant industrial era
institutions of education and training. Xers are dutifully accumulating ever more degrees,
certificates, and professional experience, reluctantly following the path of least resistance but
without conviction or much imagination. However, almost inadvertently, but consistent with
the values of tolerance and diversity proclaimed but weakly practiced by the boomers, the
Xers are being exposed to a more heterogeneous reality. They study in different countries,
learn other people’s languages (particularly English) and travel more extensively. More of
them have practiced what was preached about seeing the world, even if their mental maps
(thinking tools) for understanding it remain weak.
! Millennials could be a different story since they are beginning to live the reality of learning
anywhere, anytime, for any purpose, with anyone. They are immersing themselves in a social
and economic context of dense networking and lived complexity. They know how to put the
tools to use and do not hesitate to multi-task with asynchronous, mobile, 24/7 and global
means for communicating and knowing. Personal websites, avatars, blogs, wikis, tags,
15
telepresence, multimedia expression, and Googling are close to second nature. The classroom
school and its clones begin to fade from the picture. 72
2.3.2 Micro-level observations
One of the stronger signs in the present of significant, transformative changes in the context for
learning are not at the macro or meso level of carefully constructed aggregate indicators and
Herculean efforts at institutional reform. It is in the everyday reality of people, from all generations,
trying to cope with the freedoms and ambiguities that confront them.
Democracy, productivity, rights, and investments in the development, diffusion, and capacities
needed to wield the tools and techniques that augment our speed, strength and communication all
built the current reality. Faced with this challenge of living in a more “learning-intensive society” it
is certainly older generations like boomers, hobbled by the parameters, tools, and successes of the
past, that adapt most slowly and probably inadequately. Their anticipatory assumptions screen out
spontaneity, complexity, and emergent phenomena and solutions. The more open questions are how
much are they suffering, both from the effort to adapt and from the lack of adaptation, and how much
is their only partial adaptation and their resistance to change (passive, defensive, offensive) currently
weighing on the evolutionary process?
Gen Xers may be showing signs of the greatest difficulty. After all the boomers were raised to retire
(out to pasture to die) and even though they are not actually doing it, meaning they remain very
active in a myriad of ways, they are more willing to let go, live and let live. The Gen Xers, on the
other hand, have been saddled with many fears and constraints that reflect the decline in
effectiveness of old institutions and practices. They are inheriting the old jalopy and instead of
junking it, seem to be trying to fix it. But it is a thankless task because many of the old ways of doing
things cannot really be fixed. Both the problems and, more importantly, the surrounding conditions
have changed. But letting go is hard and it inhibits both their openness to learning and the extent of
experimentation that they actually experience. The difficulties in adapting to the learning intensity of
the present reflect a deep inability to understand and challenge their anticipatory assumptions.
Millennials are just getting started and so obviously do not have as much to lose. In this sense the
millennials do not even need to make the effort to reject the past, they are just moving on. What this
will mean for the future is unknowable since they have not done it yet. However, one aspect that can
be discerned in the present is the extent to which efforts are underway to equip the millennials based
on the emergent nature of their challenges. Here part of the answer may be this report since it is
intended to explore: the changing context for learning, the emergence of a new system of “learning
spaces,” and, last but not least, what might be done to equip people today to be better at assessing the
anticipatory assumptions that play such a major role in shaping current decision making. The
question is to what extent the millennials and perhaps the Xers will be helped by explicit efforts to
develop the capacities needed to assess current assumptions by imagining otherwise.
2.4 Technological trends and drivers
Technology occupies a privileged position in industrial societies. Strictly speaking technological
tools do not spring into the hands of people nor does a tool decide how or to what end it will be
72 SPIRE project 2007, also: Oblinger and Oblinger, 2005.
16
wielded. Yet technology is often accorded a “life” of its own, witness how it is frequently referred to
as a “driving force”. When it comes to the issue of learning technology the “driving force” is
traditionally seen as being exerted on the cost side. The printed book, the lecture hall, the blackboard,
the television, even the library are technologies or techniques for reducing the cost of diffusing
information and putting erstwhile learners in contact with teachers. Certainly the industrial take on
technology as an efficiency enhancer used by the supplier to deliver a given quality of product for a
lower cost fits the schooling model of input-output quite well. And, on this score, the story is
impressive albeit quite familiar. The next sub-section offers a selective and brief catalogue of
“techno” phenomena that have links into the transformation of the context for learning.
2.4.1 Faster, cheaper – better?
Diffusion of broadband internet access in Europe is developing quickly. However, broadband take-
up still varies widely in Europe and socio-economic factors affect broadband access and use.
However, differences in digital literacy, often as a sub-set of broader literacy issues, mean that the
introduction of broadband internet access does not provide the fix and may even deepen differences.
The signs of a growing gap between leading and lagging edges maybe good news if it means take-up
on the leading edge is going faster and farther. If this is the case it does not argue for slowing things
down; rather it puts the spotlight on efforts to ease the way further and pay closer attention to the
lagging edge.
The continuous improvement of mobile technology as an affordable technology for most citizens has
the potential of making digital interaction even more flexible, as learners can collect and
communicate images, sounds and short video on the move and use them for creating visual- and
audio-supported learning experiences for themselves and others. Wireless technologies are giving
learners the freedom to access learning resources from many different locations including ad-hoc
learning environments created on the fly.
“Free/Libre Open Source Software73 (FLOSS) is already a significant presence, providing many new
and effective tools for the net. It also motivates the development of skills, often outside official or
certified training. People participating in the development of open source software are likely to
benefit from the experience gained and can profit from the community network in many other
learning situations.74 FLOSS used for distributing, supporting and managing learning can improve
access to learning opportunities subject to the improvement of interoperability through open
standards. A significant number of initiatives are experimenting with and implementing open
educational resources, perhaps most famously at MIT through its “open courseware” initiative.75
Again, although open education is still in its infancy its significance may be as a symptom of a
systemic emergence as the old methods adapt and new ones are invented.
Looking strictly at the existing education institutions as learning spaces, investment in ICT in schools
and higher education may only be in the initial phases of take-off. Although investment in ICT in
schools has had a positive impact, there is widespread agreement that the potential has not yet been
fully realized. One of the hypotheses regarding why this is the case is that there has been too little
focus on pedagogical opportunities offered by ICT-enabled learning. Studies conclude that the
general extent of ICT integration into teaching has increased over the last 6-7 years. However, ICT is
73 Flossworld, http://www.flossworld.org/
74 OECD/CERI, 2007.
75 Source list, MIT open courseware, (http://ocw.mit.edu/index.html
17
primarily used to support existing teaching structures and methods and as a means of facilitating
communication via traditional pedagogy and didactics. So far ICT investments appear to have had
more impact on administrative services such as admissions, registrations, fee payment, and
purchasing, than on the fundamentals of teaching and learning. For now children generally use the
computer more outside the school, and they learn different ICT competences away from the school
compared to within the school. There is some hope that if teachers are more comfortable and capable
of using the new tools that there will be a more effective integration into learning activities of the
existing educational systems.76 This may or may not have implications for the more general context
for learning.
New tools also have the potential to change distance learning. So far the impact appears to be slow
and has not lead to radical changes in the way teaching and learning is conducted be it at the primary,
secondary or tertiary levels. However, due in part to cost considerations and in part to efforts at
standardization of the international higher education sector following the Bologna and Copenhagen
processes, networked learning and virtual and mobile learning environments are now increasingly on
the agenda of University management teams.77
Infrastructure convergence has the potential to improve the quality of learning experiences through
more media rich content and interactions. Companies and operators in the media field have begun
creating multimedia content across media sectors. Educational TV operated by education institutions
is more common in the US. In Europe, most initiatives draw on joint collaborative efforts between
media operators and education institutions (e.g. BBC and the Open University78 ).
Multimodal devices may create new possibilities for enriching and facilitating learning experiences.
The use of multimodal technology may help overcome the limitations imposed by small screen
mobile devices and their cumbersome data input capabilities. Podcasting and other similar
technologies are tools that can re-contextualize learning. MP3 files generated by podcasters are
relatively easy to create and do not require expensive equipment, and RSS technology enables
automatic download of new podcasts. A similar story is emerging for video. Vodcasting, the video
equivalent of podcasting and the emergence of internet based TV could redefine the way people
think about television.
In turn, this seems to have a significant potential as more and more learning takes place using high
quality video sequences, collaborative virtual worlds, and other social learning features. Ambient
Intelligence (AmI) technologies enable the development of smart rooms and intelligent spaces.
Wireless sensor networks are already able to influence the use of real world measurements, machine
learning and supervised learning. Avatar technology bridges the gap between distance learners by
allowing them to see each other and interact with one another. When brought together all of this may
give rise to one of the most powerful learning contexts – learning-by-doing in simulated
environments.
2.4.2 Technology observations
Which tools will be used, and how and by whom, remains an open question. The fascination with
technology partly induced by the cultural centrality of technology as miracle cure and partly because
76 Balanskat et.al., 2006 (EUN European Schoolnet)
77 OECD, 2005b
78 http://www.open2.net/
18
it is marketed as a cure all by everyone from high tech firms to fascinated politicians, should not
obscure the misleading nature of extrapolation in this area. Smaller, faster, better – the ICT mantra
tells little about what these tools will be used for or in what kind of society. In terms of changing the
context for learning, the available tools remain inadequate to many already existing aspirations.
Problems involve the difficulty and incompleteness of web searching, inter-operability deficiencies
that inhibit data sharing, the lack of a semantic web, the challenges concerning identity, privacy,
trust, and transparency, not to mention what many might consider the biggest limitation of all, the
poor interfaces that limit the uses of these tools. Strictly speaking only the software obstacle is really
technological in the sense of current techniques being inadequate to the task. All the rest of these
obstacles are economic, social or political and based on current performance benchmarks. These
could be overcome if many of the vested interests that defend old business models and assets, like
intellectual property rights, were less influential.79
2.5 Summary of trends and drivers
The following tables summarize a set of phenomena that may indicate a changing context for
learning. The table also includes a nominal assessment of how significant such phenomena might be
for altering the acquisition and use of learning in society, without in any way suggesting that such
impact can be predicted.
2.5.1 Impact of macro trends and drivers on learning
Trends and drivers
Main impacts in relation to learning
Globalization (very high impact) - expands the potential sources and markets for learning
- creates new learning requirements and needs
- creates a need for global standards, transparency and
collaboration, but also for localization of learning
- leads to global partnerships and consolidations in some
commercial learning markets
The emergence of new skills and
competences (high impact)
- requires learning solutions to be flexible and dynamic in order to
respond to changes in skills and competence needs.
- requires guidance of learners and learners (strongly supported) to
take control of their learning path
Demographics, health and social
changes (Very high impact)
- learning systems need to be able to cater to people with a wide
variety of different backgrounds (values, social, age, health,
learning styles, etc.)
79 Lessig, 2002.
19
20
2.5.2 Impact of meso trends and drivers on learning
Trends and drivers
Main impacts in relation to learning
Diversification of life and learning
trajectories (high impact)
- learning systems need to be able to cater for people with a wide
variety of different life trajectories (single parent family, elderly
workers, educational leave, learning while working, etc.)
- requires learning solutions to be flexible and dynamic
The educational system is only
adapting slowly to the learning
society (high impact)
Despite investments in ICT in
schools the potential of ICT is not
being fully realized
- more and more learning will take place outside the context of the
educational system
- changes will be introduced through bottom up processes initiated
by pro-active teachers and learners and large scale projects
- focus on assessing the value of investment in the use of ICT for
learning
- focus on exploiting new markets with existing educational
services
- focus on tests and evaluation of the impact of learning
- sharing of costs of resources and developments across institutions
and borders (where possible)
- may drive the change from teacher to learner centred paradigm
(learner self-service cost model) as number of students per teacher
increases in some regions/countries
- focus on developing pedagogical methodologies to take advantage
of technology enhanced learning
- greater focus on teacher training and development
- more learner centred approaches and more ICT use away from the
institution.
- learners as co-producers of learning resources
Employees at companies and
organizations learn predominantly
through informal learning (high
impact)
- focus by pioneering organizations on integration of non-formal,
formal and informal learning
- linking training offers to business results and tailoring training to
company needs.
- employers playing down the importance of non-formal and formal
learning and prioritizing informal learning instead
- status quo of supplier led learning offers not meeting demands
- focus on recognition of prior learning and work-based experience
2.5.3 Impact of micro trends and drivers on learning
Trends and drivers
Main impacts in relation to learning
Recognition of informal learning
and learning happening in several
contexts for all generations
(High impact)
- More and more learning happening in different contexts and
locations
- Focus on learning for competence development and leading to
recognition/certification
The emergence of the new
millennium learners (high impact)
- Learners seeking influence on the learning process and the role of
ICT in learning
- More and more learning happening outside the institutions
Still limited use of ICT for learning
among adults (medium impact)
- Digital divide keeping some segments of the population from
valuable learning opportunities
- Need for ICT training and guidance of certain segments of adults
3 Using a hybrid strategic scenario to imagine the future of learning
Brueghel the Elder, 1559, Staatliche Museen zu Berlin - Gemäldegalerie, Berlin Link:
http://www.ibiblio.org/wm/paint/auth/bruegel/proverbs.jpg
Scenarios are stories. As discussed below, there are many kinds of stories. The one told here is of a
particular kind. It is not about a journey, nor is it about a chain of events, a plot that leads from
intrigue to denouement. It is more like the Brueghel painting above, a snapshot of a moment in time
– a story within a frame. The learning spaces (LS) scenarios recounted here describe different ways
of looking at an imaginary tableau, one that was “painted” by a group of twenty-four people invited
to a two day workshop in Paris on February 12 and 13, 2007. The participants followed a carefully
predefined and detailed process in order to create a “living picture”. The purpose of this picture was
to provide a sufficiently detailed and functional image of learning spaces in 2020 so that by
backcasting this image onto the present it would be easier to identify and challenge the assumptions
that underpin current policy choices.
Such are the exigencies of backcasting. On the one hand, it appears similar to reverse engineering
because it involves taking something that has already been made (a picture of an imagined future),
disassembling it into its component parts to see how it works, and then comparing its functioning
with the present. This can help decision makers to compare the choices they are making now, or
those of the past, with the kinds of decisions that might be more conducive or consistent with an
imaginary future. On the other hand, this process is not at all like reverse engineering an existing
object or system because the comparator with the present does not exist.
21
Naturally, there is a temptation to try to “overcome” this problem of non-existence by developing the
most robust prediction of the future possible, which would then become the artefact to be reverse
engineered to the present. As tempting as this approach might seem, it has a fundamental flaw - not
the idea of trying to understand the present by comparing it with something different, but the hope
against better judgement that a sufficiently meaningful prediction can be made about what the
societal context for learning spaces will be like in 2020. The siren song of probabilistic thinking
needs to be meticulously overcome. The summary methodological discussion sketched in the rest of
this Chapter explains how this was done for this project.
3.1 Foresight methodology – rethinking the present
According to Météo France, the sun will rise tomorrow at 6:46. There is a fair degree of confidence
in this prediction. A meteor might hit the earth between now and then or space aliens might tow the
earth to a new location. But these are low probability events when compared to tomorrow’s sunrise.
What about the role of learning spaces in the different learning context of Europe in 2020? What can
be predicted about the status and role of learning spaces some 13 years from now? It is probably safe
to say that learning spaces will still exist and will still be playing a role in the way society functions.
Arguably, learning spaces have always been part of human societies so it is a safe bet that they will
continue to be.
Existence, however, does not tell us much about what a learning space might be like, how it might
function, and what its relationship might be to the economy and society in which it is situated. Is
there a way to predict changes in the goals of learning or in the organizational form of the institutions
that facilitate or use learning or in the ways that learning enters into the value-chain that generates
the wealth of a society? On these questions the potential for variance is very large and the number of
causal factors that might account for such variance greater still. No predictive causal model of
learning spaces exists, or at least none that we can hope has any predictive accuracy. Nor is there any
consensus on which theory might enable the construction of such a model.
Indeed, lacking an accepted theory of change in the objectives, organization and relations of learning
spaces, what options are available for this project? Is there no alternative to attempting the
impossible by building an elaborate predictive model based on an equally elaborate “scientific
theory” of the determinants and dynamics of change in learning spaces? The approach adopted here
reflects recent experiences in the field of “foresight”. The pivotal distinction is between forecasting,
a predictive exercise, and foresight, which in formal terms eschews any predictive ambitions in
favour of elaborating, more or less systematically, what we can imagine about the futures (scenarios).
There are many different types of scenarios. Most familiar are those used to plan, like in a chess
game. Here the goal is given, the resources and rules are clear, and scenarios are just different ways
of getting to the same objective. Another common type of scenario is the what-if simulation, meant
to test and improve the capacity of an emergency crew or military contingent to react to different
situations. Flight simulators for pilots are a good example of this kind of scenario training.
The learning spaces scenarios developed here do not take either of these two forms. The type of
scenario in this project is more open ended or “exploratory” – heading into unknown and
unknowable territory. In such scenario exercises there are few fixed parameters (givens). The quest,
without succumbing to the constraints of the ex ante expected or preferred, is to expand the horizons
of the possible. This way of building a scenario is open ended, a bit like life.
22
Combining the assumption that changing contexts change not only what is possible but what is
imaginable with the value statement that it would be wrong to insist that future generations must hold
the same values as we do today, eliminates one of the key expectations typically attached to a
foresight or scenario exercise. Most often the implicit (sometimes explicit) expectation of a scenario
exercise is that it will help people to change what they do today by contrasting current choices with
either a more desirable future or a more probable future.80 The normative future offers an “ideal”
benchmark, while the probable future (typically based on a pseudo-predictive model using key
driving forces) offers lessons on what to do or not to do if one wants to either accelerate or avoid the
scenario that from today’s perspective is deemed more or less probable. Both are rooted in a planning
paradigm that uses scenarios as a way to improve blueprints for the future (be it for a path over time
(time-series) or for an outcome (cross-section)).
An alternative approach, adopted here, uses scenarios as a tool for calling into question current
decisions without any expectation that the scenario used today will correspond to the scenario
developed tomorrow. Jettisoning the planning premise may seem like a subtle distinction. For
instance critics of foresight in general might point out that in any case, both in practice and in
principle, scenarios are usually assigned a low probability and hence are not a dependable planning
tool. But by altering the premise that underpins the way policy makers typically use scenarios,
particularly by explicitly not accepting the dual planning oriented imperatives of fixing a target81 for
the future and seeking the highest probability prediction (despite formal proclamations to the
contrary), the scenario method used here is at once more modest and less constrained.
Given that the aim of this paper is primarily to report the results of the learning spaces scenario
process, this is not the place to explore in any further detail the epistemological issues and
controversies that boil beneath the surface of the foresight field.
3.2 Backcasting
Like the Brueghel painting at the start of this chapter that depicts an active society, a village bursting
with human energies of all kinds in the 16th century, the following chapter describes a tableau of the
LIS of Europe in 2020 and the attributes of LS in that context. The LIS scenario paints a picture of a
social system where a specific type of learning – banal creativity – has become: the primary source
of wealth creation; the active component of identity creation and the social relationships that go with
it, and; the core of values creation as expressed through the decisions that put values into practice. It
is this picture of an imaginary learning-intensive society that provides the specific, distinctive
context for describing the workings of learning spaces in Europe in 2020. And in a backcasting
exercise like the one conducted here, it is this image of the LIS that must be
“deconstructed/reconstructed” so that the assumptions about goals, roles, and what works, are
revealed.
The Hybrid Strategic Scenario backcasting process used in this report is akin to the one used by
counterfeiters who learn how to replicate a product by taking it apart to see what it is made of and
how it works. Also called reverse engineering, this is a process that can assist the designer or
80 It is also common to use scenario exercises to build up better communication and a shared understanding of values and
expectations. But this type of scenario exercise does not usually target specific policy issues.
81 A single target because even if the scenario process generates multiple scenarios the policy choice is made in terms of avoiding the
bad scenario or achieving the good one. Sometimes policies are elaborated or judged in terms of being able to accommodate
multiple scenarios and this polyvalence is deemed a useful criterion. However this is still a planning perspective only using a set
rather than a single target.
23
decision-maker to discover how each part works and how the different parts, when fit together, make
up a working whole. Based on an assessment of how a functioning model or finished product works,
the “engineers” determine not only what it takes to replicate the item but they also pick-up clues
about how specific variations or innovations might offer new or better ways of achieving the same
ends.
Of course, in the case of learning spaces in Europe in 2020 there is no real end product to reverse
engineer, only an imaginary picture of a different context for learning, the LIS. While the Brueghel
painting presumably rests on the painter’s direct observations of the world around him, the LIS
described in Chapter 4 rests on observations of the “potential of the present” exhibited by current
phenomena as surveyed briefly and partially in Chapter 2 above. This means that quality of the
comparisons between the present and an imagined future depends a great deal on the extent to which
three partly conflicting objectives are reached: analytical rigor, imagination, and operational detail.
The process undertaken for this project took the three preceding points into account by engaging in a
carefully structured process that is described in the next sub-section.
3.3 Applying the hybrid strategic scenario process to European learning spaces in
2020
3.3.1 Two frames, a canvas, and a colour palette
In order to meet the methodological and performance criteria spelled out above a careful and detailed
process was designed and implemented for this project. This “rigorous imagining” process followed
the three steps of the “hybrid strategic scenario” approach. Each step builds on the next one in order
to create an analytically clear and imaginative set of contrasting anticipatory assumptions that reveal
the potential of the present in ways that can change decisions today.
! The first step, as specified in the following sub-section (3.3.1) and in Chapters 4 and 5
consists of four elements: a narrative frame that sets out key assumptions; a detailed
exploratory scenario of a learning-intensive society (LIS) presented in Chapter 4; a model of
learning in context that is laid out in detail in sub-section 3.3.1, part D; and a set of generic
attributes of learning spaces presented in Chapter 5.
! The second step in the process uses the material generated in the first step to engage in a
participatory scenario building exercise. The results of this process are detailed in Chapter 6.
This second step involved participants imagining how learning spaces might function in a
learning-intensive society. This stage constituted the primary contribution of the participatory
process of the workshop. This is where the value-added from the group process was created.
! The third step, summarised in Chapter 7, partly addressed by the workshop discussions and
partly by the subsequent analysis of the workshop results, teases out policy insights by
contrasting (backcasting) the detailed stories of functioning LS in a LIS, elaborated in the
second step, with existing policy assumptions.
As befits this kind of rigorous exercise both participants in the process and readers of the results as
presented in this report are able to evaluate the methods in a transparent and reproducible way. This
is a critical part of the overall approach and brings important clarity and openness to the difficult task
of anticipation or thinking about the future.
24
Learning spaces as the subject of the scenario process imposes certain requirements on how the
canvas is prepared.
First, there would be no reason to conduct a scenario exercise to imagine how learning spaces might
function in 2020 if the attributes of such a “place” – physical, virtual, social and individual – did not
change over time. After all, it is perhaps one of the most universal aspects of human society that we
learn, our advanced capacity to learn may even be considered one of the defining attributes of our
species. As a result any effort to project learning spaces into time means understanding what
distinguishes the learning space of yesterday from the learning space of tomorrow. This means that
in order to imagine the functioning of learning spaces in 2020 that are not identical to today’s
learning spaces it is essential to define learning spaces in a way that both allows and yet specifies
what is different.
Second, learning spaces, as initially defined by the report The Future of ICT and Learning in the
Knowledge Society (IPTS, 2005), are multi-dimensional, described from many different, overlapping
angles including the individual point of view, the institutional frame, and even the physical context.
As a result, in order to construct an image of functioning, operational, everyday learning spaces in
2020, the picture needs to be drawn and display the appropriate dimensions or colours. This means
that it is important to situate the scenario of learning spaces using the appropriate variables of where,
when, how, and why learning activity occurs. To return to the painting metaphor, a painting of a still-
life is neither a painting of the country side nor of village life. Looking at the Brueghel painting
reproduced at the beginning of this chapter it is clear that the things depicted, the colours used and
the relationships within the frame all describe village life at that moment in time.
Of course a painting is not only static but it also leaves out many details, some of which are implicit
in the structure or pattern of the frozen image, but others that are impossible to deduce from the
depicted moment. Furthermore, a painting is not reality. The choices made by the artist, inevitably
constrained by what he or she knows and sees (consciously and unconsciously, implicit and explicit),
are neither exhaustive nor continuous. The future is of course even more difficult – at once more
limited because there is no detail to observe and at the same time unlimited for the same reason.
Given these challenges and those of foresight in general discussed above, the approach adopted for
this process needed to be carefully defined in order to provide a sufficiently well defined frame and
painting supplies to generate a meaningful image of learning spaces in 2020.
The frame, palette of colours, and selection of subjects that serve as the basis for drawing the
learning spaces scenarios were built up using five components: a narrative frame that helps tell a
coherent story (3.3.2); a “rigorous imagining” model of the “learning-intensive society” that helps to
set the context, i.e. select the elements that serve as background (3.3.3); a model of learning in
context that helps to select the colours that will be used to paint the “protagonist” or actor in context
(3.3.4); a model of learning spaces in a learning-intensive society that combines the two models
above (points 3 and 4)(3.3.5); and lastly, specific attributes of learning spaces that help to define the
contours of the painting’s protagonists (3.3.6).
Turning once again to the Brueghel painting for a clarifying metaphor, each of these five points are
ways of specifying the nature of the story to be painted without deciding in advance the exact story
that will be told.
25
3.3.2 The narrative frame
First, there is a narrative frame that lays out the assumptions that make the story consistent – told
from a clear point-of-view, in a given genre, in a specified timeframe, and with explicit assumptions
regarding the audience and the underlying values. In the case of this exercise the specification of the
narrative frame for the scenarios is as follows:
Purpose: The aim of this scenario exercise is to discover the potential of learning spaces in a
learning-intensive society and on this basis re-examine the assumptions that shape current policy
decisions. This is a double scenario objective that mixes: a discovery-related strategic scenario of a
learning-intensive society and learning spaces within that context with ii) a backcasting scenario that
attempts to identify specific changes that might be considered enabling conditions for the functioning
of learning spaces in a learning-intensive society.
Point-of-view: The point of view for the story of learning spaces is recounted at the micro level in
terms of the conduct of daily life. The metric that offers scale to this day-in-the-life point-of view is
that of transitional or transformational change, similar to the kind of all encompassing alterations that
occurred in the shift from agriculture to industrial society. The point-of-view for the analysis is not
that of an institution or of macro-level aggregates, although obviously the changes in the conduct of
daily life have institutional and aggregate implications. The point-of-view is also that of “learning
spaces” nested within a specific societal context, which in the case of this exercise is a distinct
scenario in itself of the learning-intensive society.
Temporal frame: Comparative static cross-section in 2020 – the issue is not describing the voyage
or how or why to get from A to B.
Protagonist: the actor is the predominantly the EU (and its Member States) since the aim of the
exercise is to identify EU policies and frameworks (choices that could be made now) that would
enable/facilitate LIS-LS.82
Rules/assumptions: there are a set of general status quo assumptions regarding basic values and
social choices related to things like respect for human rights, market economy, parliamentary
democracy, etc. Additional framing assumptions: 1) Long-run change is compositional. The old co-
exists with the new, reallocation leading to shifts in the share of the total is the primary structural
attribute of long-run change. 2) All change is incremental in the sense that any change takes place in
the complex, multi-dimensional present in which inertia (power to oppose change, resistance in all its
forms) and the constraints of evolutionary functionality limit the rate of change. 3) Over time
incremental changes can produce radical differences when two points in time are compared. 4)
Change is both dialectical and usually only partially (maybe very partially) rational, explicit.
On the basis of these narrative assumptions it becomes possible to use rigorously imagined scenarios
to assess the choices that are made both at individual and collective levels in terms of the extent to
which a decision does or does not contribute to changes that refine the existing system (preservation)
versus a decision that does or does not contribute to changes that eventually, over time might
generate cumulative transformations that create a radically different, new system. It is worth noting
that the difference between preservation type decisions and transformation type decisions is always
82 The political will for this is assumed here – notionally it is what is described as the desire to create a knowledge society (e.g.
Lisbon Agenda).
26
speculative. Further, the distinction between preservation and transformation does not turn on the
question of whether or not a change is endogenous or exogenous.
Both intra- and extra-systemic changes can arise from both types of choices, although there may be a
bias in transformative choices towards enabling extra-systemic type changes if, in general, there is a
bias in transformative change towards compositional effects. For example, take the usual type of
reform efforts undertaken by governments to improve education or health care or social insurance or
labour market flexibility – most of these kinds of changes are intra-systemic and can be characterized
as efforts to preserve the system by making it work better. Without in any way impugning the desire
to improve efficiency and outcomes by refining an existing system, such reforms may end up
contributing to transformation because they ignore or even oppose the development of extra-systemic
practices. Such is the nature of compositional change and of the uneasy, often conflictive relationship
between the status quo and the emergent.
3.3.3 The “learning-intensive society” frame
Second, the context chosen for situating the learning spaces scenario is itself a detailed scenario of a
society where the predominant technological, economic, social, and governance characteristics have
changed. All societies, at any time, are composed of many different layers, of different more or less
depreciated vintages; for instance, that industrial society coexisted with elements agricultural society.
The transition from one dominant system to another does not entirely do away with the past. Rather,
it is assumed here that societies are composed of sets of dynamic systems that evolve through both
endogenous and exogenous processes, and that at different points in time different systems and
different processes have different degrees of importance for the direction and day to day functioning
of the social system as a whole. Such ecologies evolve in complex and compositional ways.
The LIS is a scenario that describes a static moment in a general social system where the old
industrial sub-system and processes no longer predominate. The question is how to describe what
does. Providing such a description, inevitably leaning on terms and logics that are still largely
industrial, means being able to answer the following questions in ways that distinguish the LIS from
the present:
! With respect to the creation, exchange and accumulation of wealth (value) - what are the main
attributes of wealth (tangible or intangible, homogeneous or heterogeneous) and of its
organization?
! What kinds of property rights predominate (diversity of contractual relationships, mix of
different degrees of copyright/copyleft)? How does this relate to business models (ways of
making a profit)?
! How is trust established and maintained in different spheres of economic, social and collective
inter-action and choice?
! How does work (or wealth creating activity) relate to the way we build our habitat?
! How is power allocated (is authority assigned or taken, is decision making capacity gained
through experimentation, is complexity embraced)?
! What kind of equality matters (hierarchy and/or heterarchy)?
! What shapes a person’s identity?
! How is risk perceived & managed?
! What are the enabling or collective attributes of the LIS?
27
! What do people need to know – know-what, know-how, know-who, know-why?
The learning-intensive society as the context for developing specific descriptions of learning spaces
can be summarized very succinctly following only the most primary (colours) aspects, along the
following lines:
! Technology - Ambient computing – high levels of ease-of-use, range-of-uses for information
technologies such that these tools are no longer “evident”;
! Economy: Unique creation – high levels of unpredictability of tasks and freedom of initiative
for wealth creating activity mean that the predominant source of value-added is the refinement
of taste (banal creativity);
! Society: Bottom-up collective identity – high levels of diversity of affiliations and intensity of
identity generating decision making produce sense making that integrates (internalizes) the
social nature of the individual; and
! Governance: High levels of transparency/access to information and experience in making
strategic choices emerges reflexively from the interaction of ambient computing, unique
creation and bottom-up collective identity.
The descriptive short version: The LIS is about daily life when:
! Information technology is ambient and ubiquitous, the use, not the tool, requires skill;
! Unique creation predominates in a high transaction intensity, post-subsistence, quality of life
economy;
! Identity is bottom-up, highly heterogeneous, produced endogenously on a highly liberating
minimum common denominator of values, and;
! Decision making capacity allows people to embrace experimentalism, heterogeneity,
complexity, and spontaneity.
3.3.4 A model of learning
Third is a model of learning that provides the basis for describing learning in different contexts – this
is a model that is not bounded by the definition of its variables in a specific historical period.
Workshop participants were provided with two “situational” schemas for defining learning. The first,
following the work of Etienne Wenger’s social theory of learning (diagram below),83 takes an
action/function perspective on learning. On the action side there is learning as: doing, belonging,
becoming, and experience. On the function side there is learning as: practice, community, identity,
and meaning. Such a model is situational in the sense that the actions and functions, such as the way
a person belongs or practices, depend on the historical context and the actual acts. This situational
model for describing learning is perfectly suited to the task of painting scenarios.
83 Wenger, 1999.
28
Etienne Wenger’s Diagram of Learning
In a similar fashion, the model proposed by Ilkka Tuomi in the original IPTS Learning Spaces
document84 situates learning in a way that makes action in context the fulcrum of learning. Tuomi
stresses the temporality of learning by distinguishing the cumulative and anticipatory dimensions as
well as the modalities used to formulate learning, including articulation and conceptualization. This
model helps to include within the contextual description of learning the tools and media that mediate
the relationship between the learner and the world around them. These too are highly context-specific
and need to be described for the learning spaces of the learning-intensive society in 2020. However,
and this is a crucial point, these mediating tools, that include language (as per Tuomi’s diagram
below), do not put the technology forward as a driving force.
84 Punie and Cabrera, 2006.
29
Source: Tuomi, 2006, p. 81.
On the contrary, these models stress that it is the context which gives specificity to the actions,
power, temporality, and formulation that are learning, not the tools. These learning models help shift
the emphasis away from the no doubt fascinating but epiphenomenal aspects of the “new” to the
more prosaic but also more substantive dimensions of what people actually do and for what purpose.
3.3.5 Combining the learning model with the learning-intensive society model
Fourth, by taking the two prior models, one of the learning-intensive society and the other of learning
as a social activity, it is possible to define an analytical frame for the specific story we are trying to
paint, i.e. of learning spaces in a learning-intensive society in 2020. Merging the two models
produced the following functional relationships as a way to describe the context within which LS
work in the context of the LIS.
In the context of a learning-intensive society all of the learning spaces scenarios are located at the
outer rim of the radar chart below. Putting learning spaces in the LIS context allows for a more
detailed description of the specific attributes and functioning. This specification of the attributes of
LS in an LIS was used to conduct the “rigorous imagining” process with participants to the process at
a two day workshop in Paris in February 2007.
30
31
Learning Spaces Model Radar Chart
Wealth Creation
3.3.6 A generic palette of colours for describing learning spaces
Fifth is the descriptive attributes of learning spaces as provided by the original IPTS report and
elaborated in detail in Chapter 5. These categories are generic ones that can be used to describe
learning in a wide range of contexts and points in time, from ancient Rome to the jungles of
Columbia. Once learning is anchored in a specific historical and physical context, this list serves as a
sort of colour code to help descriptively paint the details (think here of the way colours are used on
maps to highlight specific features or how in paintings we easily make an association of flesh colours
with skin, white with clouds and blue with water).
0
1
2
3
4
5
6
7
8
9
10
Quality of
Learning
Resources
Identity
Mass- era
Learning society
Efficiency
of Learning
Resources
Active Learning
Reflective Learning
4 Imagining the future of learning
Learning Spaces (LS) are the next school. That is the rigorously imagined scenario explored by this
report. It is a vision of learning that differs radically from the conventional classroom image above –
where blackboard knowledge and the imposing teacher represent the quintessential learning space of
the industrial era. Instead, because the context for learning is different, learning spaces are much
closer to the radical message from the film Happy Feet cited at the outset of this report. In that movie
the primary learning task is to find your “Heart Song,” and to do so “all by yourself”. In this film,
which is the story of a Penguin searching for his identity, inner knowledge is validated instead of
denigrated. Learning is about finding out “who you truly are” from the “voice you hear inside”.
What is the test of learning in Happy Feet? Performance is the test, the act of singing your song to
the community. Not as an externally set exam, but as a song that is your own, one that is refined and
embroidered for an entire lifetime as part of a societal symphony. Indeed the film goes even further
since the hero of the story does not have a song but a dance. The film’s message is to learn to express
yourself in the way that suits you, not to some pre-ordained community standard but to one’s own
sense of self. The story is about a community of learning-intensive penguins that learn to be open to
open learning.
The scenario of a 21st Century Learning-intensive Society depicted in this report is an imaginary
snapshot of how society might function with open learning at the core of what everyone does all the
time, everywhere. This scenario is neither a prediction nor a statement of desirability, but an
imaginary picture of what learning is like in Europe in 2020. It is this imaginary scenario that fulfils
the requirement, stipulated in John Dewey’s statement quoted at the beginning of the report, that the
“conception of education as a social process” requires a prior definition of “the kind of society”
within which the learning occurs. The context for learning is critical and the scenario developed in
this Section provides that different context.
From the outset, it is important to underscore that this image of learning, as it occurs in everyday life
in Europe in 2020, is not a scenario of how the image came to be. It is a painting not a movie.
Without belabouring the technicalities of “thinking about the future”, the foresight methodology
adopted for this report uses a “comparative static back-casting” approach.85 What this means is that
the focus is on generating and comparing two tableaux – one of an imaginary society in 2020 and the
other the Europe of today. The process for generating this comparison entailed the elaboration of
detailed preparatory analyses and stage-setting papers, an intensive two day workshop with over
twenty international experts in education and foresight, and a careful refinement and elaboration of
the results for this report, including further feedback and inputs from a range of experts.
The point of comparing two moments in time is not to find the line between them, the path from A to
B. Nor is the intention to describe the results of an intricate, highly technical exercise in prediction
that provides a “scientific” “best guess” of what the future will be like. Such efforts are not only
illusory but also misleading.86 The aim of the exercise is to find a way to gain a better understanding
85 Much back-casting work, pioneered by John Robinson (see bibliography, Robinson 1990, and one of the participants in this
process), is used to trace a path back from the future to the present and thereby discover one way of getting from A to B. The
approach adopted here is less ambitious, aiming to compare two points in time – one an imaginary future and the other the present.
A few observations on intermediary steps are offered in the conclusions to this report, but there is no predictive accuracy claimed
for such statements since they simply offer a logical “what-if” extrapolation based on the comparative static comparison.
86 Miller, 2006b.
33
of the assumptions people use when they make choices. This is a crucial anticipatory component of
choice, any choice, from the everyday kind of decision to take an umbrella because of an assumption
about the probability of rain to the grand kinds of choices about the fundamental legal, institutional,
and moral infrastructure of a society.
The Hybrid Strategic Scenario (HSS) method87 used in this process generates a “rigorously
imagined” scenario that throws into sharp relief the fixed ideas (anticipatory assumptions) – typically
“inside-the-box” conceptual building blocks – that play a strong role in shaping decisions. For
example, in the scenario elaborated for this report the learning infrastructures that have served
industrial societies so brilliantly are marginal. Compulsory classroom-based schools, apprentice and
skilled trades training systems, adult education, and mass-universities, are still part of the landscape
but, relative to past glory, much less significant. Instead, in the predominant position formerly
occupied by industrial era learning institutions for well over a century, there is a new system that
provides the infrastructure to support a much more multi-dimensional, holistic, and omnipresent
societal role and everyday practice for learning.
The Learning Spaces (LS) of 2020 function on different principles and achieve different objectives
than the education systems of 2008.88 Two fundamental differences distinguish the education
systems that are characteristic of today’s industrial era from the LS that are predominant in the
scenarios used to describe European society in 2020. One is related to purpose - or the function of
learning - and the other is related to organization - or how learning takes place
! The first arises from the clear dominance of a transformation in what and how wealth is created
and social well-being sustained. This is a change in the socio-economic context for learning.
! The second reflects a shift, not so much in the way learning has always happened – actively –
but in the way the recognition and pursuit of the activity that is learning are integrated into
everyone’s everyday life, all the time. This is a change in the organization of learning activities
and the infrastructure that facilitates those activities.
In 2020, LS are mostly about how people as inter-dependent and inter-connected social beings
construct their identity and, on this basis, produce the wealth and community that sustains their well-
being. In general terms this functional role or purpose of learning infrastructure in 2020 is not much
different from before, continuing to serve the main economic and social requirements of society.
However, by 2020 the leading economic and social requirements have changed. In the scenario of
post-subsistence society in 2020 dubbed “The Learning-intensive Society” (LIS), the leading source
of wealth (value/utility), increased productivity, and social cohesion, is an activity called “unique
creation.”89
4.1 The learning-intensive society (LIS) scenario
The image of European societies in 2020 depicted in the LIS scenario is one where daily life has
moved beyond today’s dawning recognition of what it means to be post-subsistence and post-
87 Miller, 2007a.
88 For convenience of exposition for the rest of this report, the term “education system” will be used to refer to the predominant
“learning spaces” of the industrial era, and the term Learning Spaces (LS) will be used to refer to the systems for facilitating
learning that are in a leadership position in the scenarios of 2020 developed in this report.
89 Miller and Bentley, 2002; Prahalad and Ramaswamy, 2004; Toffler and Toffler, 2006.
34
industrial. In 2020, the old industrial society, including everything from manufacturing to services
like banking, health care, and education, all historically organized on industrial lines, is looked upon
in much the same way as agriculture was in the 20th century. In the industrial era, farming and rural
life played a role, perhaps somewhat greater than its actual weight in economic and social affairs
merited, but there was little question that leadership and pre-eminence from the point of view of
societal change had passed to industry. In 2020, the relationship between the LIS and industrial past
is similarly unequal, with the LIS taking the lead.
In the imaginary snapshot of Europe in 2020 it is assumed that society is no longer dominated by the
industrial-era logics of mass-production and mass-consumption. Scale is no longer the guiding
principle. Instead, the pivotal act, the creation of value-added, has changed locations. In the LIS of
2020 the daily (re)creation of the world around us – things, services, and relationships – generates
the largest share of value-added through self-generated personalization – “unique creation:” DIY
(do-it-yourself), Pro/Am (professional/amateur), Web 2.0 (social networking), democratized
innovation, etc. These forms of production are all weak signals in 2008, hints of the potential of the
present to go beyond, mass-production/mass-consumption to create a society where the division
between the supply side and demand sides is marginal.
This means that the crucial moment in industrial society when the entrepreneur or engineer or
designer comes up with an idea (conceived) that can then be implemented (executed) by taking
advantage of economies of scale is no longer central. The aims and organization of wealth creation
no longer take on the form of a pyramid or hierarchy, with the genius who generates new ideas and
the technocrat manager who implements them occupying the top floor, while down below at end of
the chain of command is the “front-line” worker. The LIS is heterarchical (antonym of hierarchical).
Everyone is the inventor and implementer of his or her own designs, the unique, personalized set of
artefacts, services, and experiences. As a result, in the LIS there is a profound difference when
compared to industrial society in the relationship of knowledge to production or, in more general
terms, the activities that (re)create daily life.
In a socio-economic system dominated by “unique creation” the critical value-added comes from the
ideas and insights that each person makes as their contribution to the (re)creation of everyday life (a
process that is inherently inter-personal, networked). The nature and source of this personalized
value-added is not and need not be the genius of industrial era success typified by the brilliant
entrepreneur or technocrat who in a flash of exceptional insight (implemented through command and
control leadership) determines what and how to produce the goods and services that keep everyone
else busy working and consuming. On the contrary, with “unique creation” it is a simpler, more
imitative and shared set of tastes that gets refined gradually through experience (learning-by-doing)
that is the dominant source of activity and value-added. People still spend a fair share of their time
creating wealth, but this wealth is related to outputs and process that add value to their identity and
community, i.e. what matters to them.
Such a shift unthrones the kings of the industrial era, those at the top of the pyramid of value creation
– the mass-market designers, inventors, and managers. Instead, it is the everyday, everywhere “banal
creativity” of self-actualization that creates value in the broadest sense of things, services, and
experiences that are desired/useful/satisfying. In the LIS, not only is the universe of “economically”
relevant outputs and transactions expanded beyond today’s GNP or monetary realm,90 but equally as
90 Typical measures of wealth consisting of GDP and productivity do not take into account many components of well-being.
Alternative indicators are being developed, such as the Happy Planet index (New Economics Foundation, 2006) or the World
35
crucial, the origin of efficiency improvement (productivity growth) is in the refinement of taste –
knowing ever more exactly why and what you and your community want. From the point-of-view of
learning it is “truth through experience” (xperidox) or “learning-by-doing” that dominates.
Consequently, LS are at the core of the economy and society.
In the open, trusted and connected context that makes LS work, the imperatives that seemed so
urgent in 2008, like yoking education to the idea of “national competitiveness,” have receded into an
old memory. In this LIS scenario of 2020 both old industrial style learning and the notion of national
competitiveness are passé. Why? Because it is widely unders